Research

I am interested in all combinations of machine learning, natural language processing, and healthcare.

Some themes of my research include:

Natural language processing

Brain data

Explainable models

Machine learning

Human-robot interaction

Healthcare

Fairness, privacy, and ethics of AI

Publications

BooksChaptersJournalsRefereed conferences and workshopsOther

Books

Clear speech: Technologies that enable the expression and reception of language.
Frank Rudzicz.
Morgan & Claypool, 2016.
[URL] [BIB]

Chapters

Machine learning for medicine.
Frank Rudzicz.
In: Artificial Intelligence in Surgery: A Primer for Surgical Practice, Dan A Hashimoto, editor., McGraw Hill, New York, NY, ISBN: 978-1260452730, 2021.
[URL] [BIB]
Ethics of artificial intelligence in surgery.
Frank Rudzicz and Raeid Saqur.
In: Artificial Intelligence in Surgery: A Primer for Surgical Practice, Dan A Hashimoto, editor., McGraw Hill, New York, NY, ISBN: 978-1260452730, 2021.
[URL] [BIB]
Explainable AI for the Operating Theater.
Frank Rudzicz and Shalmali Joshi.
In: Digital Surgery, Sam Attalah, editor., Springer, ISBN: 978-3-030-49100-0, 2020.
[URL] [BIB]

Journals

Improving estimates of pertussis burden in ontario, canada 2010-2017 by combining validation and capture-recapture methodologies.
Shilo H McBurney, Jeffrey C Kwong, Kevin A Brown, Frank Rudzicz, Andrew Wilton, and Natasha S Crowcroft.
PLOS ONE, , 2024.
[BIB]
Context is not key: detecting alzheimer’s disease with both classical and transformer-based neural language models.
Behrad TaghiBeyglou and Frank Rudzicz.
Natural Language Processing Journal, , 2024.
[BIB]
Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof‐of‐concept.
Anton Nikouline, Jinyue Feng, Frank Rudzicz, Avery Nathens, and Brodie Nolan.
European Journal of Trauma and Emergency Surgery, , 2024.
[URL] [BIB]
Feature extraction for exoplanet detection.
Joao Pimentel, Joana Amorim, and Frank Rudzicz.
International Journal of Data Science and Analytics, , 2024.
[URL] [BIB]
Length of stay prediction models for oral cancer surgery: machine learning, statistical and ACS-NSQIP.
Amirpouyan Namavarian, Alexander Gabinet-Equihua, Yangqing Deng, Shuja Khalid, Hedyeh Ziai, Konrado Deutsch, Jingyue Huang, Ralph W. Gilbert, David P. Goldstein, Christopher M.K.L. Yao, Jonathan C. Irish, Danny J. Enepekides, Kevin M. Higgins, Frank Rudzicz, Antoine Eskander, Wei Xu, and John R. de Almeida.
The Laryngoscope, , 2024.
[URL] [BIB]
Depression-anxiety coupling strength as a predictor of relapse in major depressive disorder: a CAN-BIND wellness monitoring study report.
Abraham Nunes, Barbara Pavlova, Jasmyn Cunningham, John-Jose Nuñez, Lena C. Quilty, Jane Foster, Keith Ho, Raymond W. Lam, Valerie H. Taylor, Roumen Milev, Susan Rotzinger, Claudio N. Soares, Kate L. Harkness, Gustavo Turecki, Sidney Kennedy, Benicio N. Frey, Frank Rudzicz, and Rudolf Uher.
Journal of Affective Disorders, , 2024.
[BIB]
The Genetics Navigator: Protocol for a mixed methods randomized controlled trial evaluating a digital platform to deliver genomic services.
Guylaine D'Amours, Marc Clausen, Stephanie Luca, Emma Reble, Rita Kodida, Daniel Assamad, François Bernier, Lauren Chad, Gregory Costain, Irfan Dhalla, Hanna Faghfoury, Jan Friedman, Stacey Hewson, Trevor Jamieson, Josh Silver, Cheryl Shuman, Matthew Osmond, June C Carroll, Rebekah Jobling, Anne-Marie Laberge, Melyssa Aronson, Eriskay Liston, Jordan Lerner-Ellis, Christian Marshall, Michael Brudno, Quynh Pham, Frank Rudzicz, Ronald Cohn, Muhammad Mamdani, Maureen Smith, Serena Shastri-Estrada, Emily Seto, Kevin Thorpe, Wendy J. Ungar, Robin Hayeems, and Yvonne Bombard.
BMJ Open, , 2024.
[BIB]
The utility and implications of ambient scribe in primary care.
Puneet Seth, Romina Carretas, and Frank Rudzicz.
JMIR AI, , 2024.
[BIB]
From the screen to the streets: technology-facilitated violence against public health professionals.
Cheryl Regehr, Kaitlyn Regehr, Vivek Goel, Kelly Lyons, and Frank Rudzicz.
Journal of Loss and Trauma, , 2024.
[BIB]
Deep learning model for automated practitioner assessment during high-fidelity simulation.
Asad Siddiqui, Zhoujie Zhao, Chuer Pan, Frank Rudzicz, and Tobias Everett.
Academic Medicine, 98(11):1274-1277, 2023.
[URL] [BIB]
Exploring the use of natural language processing for objective assessment of disorganized speech in schizophrenia.
Lydia Jeong, Melissa Lee, Ben Eyre, Aparna Balagopalan, Frank Rudzicz, and Cedric Gabilondo.
Psychiatric Research and Clinical Practice, 5(3):84-92, 2023.
[URL] [BIB]
Contextualizing the tone of the operating room in practice: drawing on the literature to connect the dots.
Hillary Lia, Melanie Hammond Mobilio, Frank Rudzicz, and Carol-anne Moulton.
Frontiers in Psychology, 14(1167098), 2023.
[URL] [BIB]
Brain imaging signatures of neuropathic facial pain derived by artificial intelligence.
Timur H. Latypov, Matthew C. So, Peter Shih-Ping Hung, Pascale Tsai, Matthew R Walker, Sarasa Tohyama, Marina Tawfik, Frank Rudzicz, and Mojgan Hodaie.
Nature Scientific Reports, 13(10699), 2023.
[URL] [BIB]
Data science as a core competency in undergraduate medical education in the age of ai in healthcare.
Puneet Seth, Nancy Hueppchen, Steven D Miller, Frank Rudzicz, Jerry Ding, Kapil Parakh, and Janet D Record.
JMIR Medical Education, , 2023.
[URL] [BIB]
Workplace violence in the covid era: a qualitative analysis of harassment and threats against public health professionals in canada.
Cheryl Regehr, Kaitlyn Regehr, Vivek Goel, Christa Sato, Kelly Lyons, and Frank Rudzicz.
BMJ Public Health, , 2023.
[URL] [BIB]
It’s not the arrow, it’s the archer: the role of the surgeon leader in a safety driven-era.
Hillary Lia, Melanie Hammond Mobilio, Frank Rudzicz, and Carol-anne Moulton.
Surgical Endoscopy, , 2023.
[BIB]
Differential expression of a brain aging biomarker across discrete chronic pain disorders.
Peter Shih-Ping Hung, Jia Y Zhang, Alborz Noorani, Matthew R Walker, Megan Huang, Jason Zhang, Normand Laperriere, Frank Rudzicz, and Mojgan Hodaie.
PAIN, , 2022.
[URL] [BIB]
A Delphi consensus statement for digital surgery.
Kyle Lam, Michael D. Abràmoff, José M. Balibrea, Steven M. Bishop, Richard R. Brady, Rachael A. Callcut, Manish Chand, Justin W. Collins, Markus K. Diener, Matthias Eisenmann, Kelly Fermont, Manoel Galvao Neto, Gregory D. Hager, Robert J. Hinchliffe, Alan Horgan, Pierre Jannin, Alexander Langerman, Kartik Logishetty, Amit Mahadik, Lena Maier-Hein, Esteban Martín Antona, Pietro Mascagni, Ryan K. Mathew, Beat P. Müller-Stich, Thomas Neumuth, Felix Nickel, Adrian Park, Gianluca Pellino, Frank Rudzicz, Sam Shah, Mark Slack, Myles J. Smith, Naeem Soomro, Stefanie Speidel, Danail Stoyanov, Henry S. Tilney, Martin Wagner, Ara Darzi, James M. Kinross, and Sanjay Purkayastha.
Nature Digital Medicine, 5(100), 2022.
[URL] [BIB]
Predicting the target specialty of referral notes to estimate per-specialty wait times with machine learning.
Mohamed Abdalla, Hong Lu, Bogdan Pinzaru, Frank Rudzicz, and Liisa Jaakkimainen.
PLoS ONE, , 2022.
[URL] [BIB]
Conformal mirror descent with logarithmic divergences.
Amanjit Singh Kainth, Ting-Kam Leonard Wong, and Frank Rudzicz.
Information Geometry, , 2022.
[URL] [BIB]
Modified subspace constrained mean shift algorithm.
Youness Aliyari Ghassabeh and Frank Rudzicz.
Journal of Classification, 38:27--43, 2021.
[URL] [BIB]
Deep learning for voice gender identification: proof-of-concept for gender-affirming voice care.
Yael Bensoussan, Jeremy Pinto, Matthew Crowson, Patrick R. Walden, Frank Rudzicz, and Michael Johns III.
Laryngoscope, 131(5):E1611-E1615, 2021.
[URL] [BIB]
Using machine learning to predict children's reading comprehension from linguistic features extracted from speech and writing.
Jeanne Sinclair, Eunice E Jang, and Frank Rudzicz.
Journal of Educational Psychology, 113(6):1088--1106, 2021.
[URL] [BIB]
Machine learning–based prediction of growth in confirmed COVID-19 infection cases in 114 countries using metrics of nonpharmaceutical interventions and cultural dimensions: model development and validation.
Arnold YS Yeung, Francois Roewer-Despres, Laura Rosella, and Frank Rudzicz.
JMIR, 23(4):e26628, 2021.
[URL] [CODE] [BIB]
Comparing pre-trained and feature-based models for prediction of Alzheimer's disease based on speech.
Aparna Balagopalan, Benjamin Eyre, Jessica Robin, Frank Rudzicz, and Jekaterina Novikova.
Frontiers in Aging Neuroscience, 13, 2021.
[URL] [BIB]
Regional brain morphology predicts pain relief in trigeminal neuralgia.
Peter Shih-Ping Hung, Alborz Noorani, Jia Y. Zhang, Sarasa Tohyama, Normand Laperriere, Karen D. Davis, David J. Mikulis, Frank Rudzicz, and Mojgan Hodaie.
NeuroImage: Clinical, 31:102706, 2021.
[URL] [BIB]
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data.
Demetres Kostas, Stéphane Aroca-Ouellette, and Frank Rudzicz.
Frontiers in Human Neuroscience, 15, 2021.
[URL] [BIB]
Population-based incidence of invasive pneumococcal disease in children and adults in Ontario and British Columbia, 2002–2018: a Canadian Immunization Research Network (CIRN) study.
Sharifa Nasreen, Jun Wang, Jeffrey C. Kwong, Natasha S. Crowcroft, Manish Sadarangani, Sarah E. Wilson, Allison McGeer, James D. Kellner, Caroline Quach, Shaun K. Morris, Beate Sander, Julianne V. Kus, Monika Naus, Linda Hoang, Frank Rudzicz, Shaza Fadel, and Fawziah Marra.
Vaccine, 39(52):7545-7553, 2021.
[URL] [BIB]
Four equity considerations for the use of artificial intelligence in public health.
Maxwell J Smith, Renata Axler, Sally Bean, Frank Rudzicz, and James Shaw.
Bulletin of the World Health Organization, 98(4):290--292, 2020.
[URL] [BIB]
A conversational robot for older adults with Alzheimer's disease.
Chloé Pou-Prom, Stefania Raimondo, and Frank Rudzicz.
ACM Transactions on Human-Robot Interaction, 9(3):1--25, 2020.
[URL] [BIB]
Evaluation of deep learning models for identifying surgical actions and measuring performance.
Shuja Khalid, Mitchell Goldenberg, Teodor Grantcharov, Babak Taati, and Frank Rudzicz.
JAMA Network Open, 3(3):e201664, 2020.
[URL] [BIB]
A textual analysis of US corporate social responsibility reports.
Peter M Clarkson, Jordan Ponn, Gordon D Richardson, Frank Rudzicz, Albert Tsang, and Jingjing Wang.
Abacus, 56(1):3--34, 2020.
[URL] [BIB]
Using word embeddings to improve the privacy of clinical notes.
Mohamed Abdalla, Moustafa Abdalla, Frank Rudzicz, and Graeme Hirst.
Journal of the American Medical Informatics Association (JAMIA), 27(6):901--907, 2020.
[URL] [BIB]
Exploring the privacy-preserving properties of word embeddings: algorithmic validation study.
Mohamed Abdalla, Moustafa Abdalla, Graeme Hirst, and Frank Rudzicz.
JMIR, 22(7):e18055, 2020.
[URL] [BIB]
Evaluation of speech-based digital biomarkers: review and recommendations.
Jessica Robin, JE Harrison, Liam D Kaufman, Frank Rudzicz, William Simpson, and Maria Yancheva.
Digital Biomarkers, 4:99--108, 2020.
[URL] [BIB]
Thinker invariance: enabling deep neural networks for BCI across more people.
Demetres Kostas and Frank Rudzicz.
Journal of Neural Engineering, 17(5), 2020.
[URL] [BIB]
Exploring interface design to support caregivers' needs and feelings of trust in online content.
Thana Hussein, Preet K Chauhan, Nicole K Dalmer, Frank Rudzicz, and Jennifer Boger.
Journal of Rehabilitation and Assistive Technologies Engineering, 7, 2020.
[URL] [BIB]
MySurgeryRisk and Machine Learning: A Promising Start to Real-time Clinical Decision Support.
Lauren Gordon, Peter Austin, Frank Rudzicz, and Teodor Grantcharov.
Annals of Surgery, 269(1):14--15, 2019.
[URL] [BIB]
Privacy versus artificial intelligence in medicine.
Taryn J Rohringer, Akshay Budhkar, and Frank Rudzicz.
University of Toronto Medical Journal, 96, 2019.
[BIB]
Machine learning for MEG during speech tasks.
Demetres Kostas, Elizabeth Pang, and Frank Rudzicz.
Nature Scientific Reports, 9(1609), 2019.
[URL] [CODE] [BIB]
Talk2Me: Automated linguistic data collection for personal assessment.
Majid Komeili, Chloé Pou-Prom, Daniyal Liaqat, Kathleen C Fraser, Maria Yancheva, and Frank Rudzicz.
PLoS ONE, 14(3):e0212342, 2019.
[URL] [DATA] [CODE] [BIB]
Artificial intelligence and the implementation challenge.
James Shaw, Frank Rudzicz, Trevor Jamieson, and Avi Goldfarb.
JMIR, 21(7):e13659, 2019.
[URL] [BIB]
Explainable artificial intelligence for safe intraoperative decision support.
Lauren Gordon, Teodor Grantcharov, and Frank Rudzicz.
JAMA Surgery, 154(11):1064-1065, 2019.
[URL] [BIB]
Automatically determining cause of death from verbal autopsy narratives.
Serena Jeblee, Mireille Gomes, Prabhat Jha, Frank Rudzicz, and Graeme Hirst.
BMC Medical Informatics and Decision Making, 19(127), 2019.
[URL] [BIB]
Accessible data, health ai, and the human right to benefit from science and its applications.
Marzyeh Ghassemi, Anna Goldenberg, Quaid D Morris, Frank Rudzicz, Bo Wang, Richard Zemel, Elham Dolatabadi, Garth A Gibson, and P Alison Paprica.
Health Law in Canada, 40(1):37--43, 2019.
[URL] [BIB]
A survey of word embeddings for clinical text.
Faiza Khan Khattak, Serena Jeblee, Chloé Pou-Prom, Mohamed Abdalla, Christopher Meaney, and Frank Rudzicz.
Journal of Biomedical Informatics, 100, 2019.
[URL] [BIB]
Development of a ternary hybrid fNIRS-EEG brain–computer interface based on imagined speech.
Alborz Rezazadeh Sereshkeh, Rozhin Yousefi, Andrew T Wong, Frank Rudzicz, and Tom Chau.
Brain-Computer Interfaces, 6(4):128--140, 2019.
[URL] [BIB]
A novel approach for acoustic estimation of neck fluid volume between men and women.
Mehrnaz Shokrollahi, Frank Rudzicz, Daniel Vena, T Douglas Bradley, and Azadeh Yadollahi.
Medical & Biological Engineering & Computing, 56(1):113-123, 2018.
[URL] [BIB]
NeuroSpeech: An open-source software for Parkinson's speech analysis.
Juan Rafael Orozco-Arroyave, Juan Camilo Vásquez-Correa, Jesús Francisco Vargas-Bonilla, Raman Arora, N.Dehak, PS Nidadavolu, Heidi Christensen, Frank Rudzicz, Maria Yancheva, Hamidreza Chinaei, A Vann, N Vogler, T Bocklet, M Cernak, J Hannink, and Elmar Nöth.
Digital Signal Processing, 77:207--221, 2018.
[URL] [CODE] [BIB]
Feasibility of using a smartwatch to intensively monitor patients with chronic obstructive pulmonary disease: prospective cohort study.
Robert Wu, Daniyal Liaqat, Eyal de Lara, Tatiana Son, Frank Rudzicz, Hisham Alshaer, Pegah Abed-Esfahani, and Andrea S Gershon.
JMIR Mhealth Uhealth, 6(6), 2018.
[URL] [BIB]
Modified mean shift algorithm.
Youness Aliyari Ghassabeh and Frank Rudzicz.
IET Image Processing, 12(12):2172--2177, 2018.
[URL] [BIB]
Identifying and avoiding confusion in dialogue with people with Alzheimer's disease.
Hamidreza Chinaei, Leila Chan Currie, Andrew Danks, Hubert Lin, Tejas Mehta, and Frank Rudzicz.
Computational Linguistics, 43(2):377--406, 2017.
[URL] [BIB]
The effect of photoperiod on the mood of Reddit users.
Kawin Ethayarajh and Frank Rudzicz.
Cyberpsychology, Behavior, and Social Networking, 20(4):238--245, 2017.
[URL] [BIB]
Characterisation of voice quality of Parkinson's disease using differential phonological posterior features.
Milos Cernak, Juan Rafael Orozco-Arroyave, Frank Rudzicz, Heidi Christensen, Juan Camilo Vásquez-Correa, and Elmar Nöth.
Computer Speech & Language, 46:196--208, 2017.
[URL] [BIB]
Rhetorical structure and Alzheimer's disease.
Mohamed Abdalla, Frank Rudzicz, and Graeme Hirst.
Aphasiology, 32(1):41--60, 2017.
[URL] [BIB]
Toward dementia diagnosis via artificial intelligence.
Frank Rudzicz.
Today's Geriatric Medicine, 9(2):8, 2016.
[URL] [BIB]
Speech production in speech technologies.
Karen Livescu, Frank Rudzicz, Eric Fosler-Lussier, Mark Hasegawa-Johnson, and Jeff Bilmes.
Computer Speech & Language, 36:165--172, 2016.
[URL] [BIB]
Manifold learning for multivariate variable-length sequences with an application to similarity search.
Shen-Shyang Ho, Peng Dai, and Frank Rudzicz.
IEEE Transactions on Neural Networks and Learning Systems, 27(6):1333 -- 1344, 2016.
[URL] [BIB]
Linguistic Features Identify Alzheimer’s Disease in Narrative Speech.
Kathleen C Fraser, Jed A Meltzer, and Frank Rudzicz.
Journal of Alzheimer's Disease, 49(2):407--422, 2016.
[URL] [BIB] Baycrest Research in Print award
Principal differential analysis for detection of bilabial closure gestures from articulatory data.
Farook Sattar and Frank Rudzicz.
Computer Speech & Language, 36:294--306, 2016.
[URL] [BIB]
Prosody and semantics are separate but not separable channels in the perception of emotional speech: test for rating of emotions in speech.
Boaz M Ben-David, Namita Multani, Vered Shakuf, Frank Rudzicz, and Pascal HHM van Lieshout.
Journal of Speech, Language, and Hearing Research, 59(1):72--89, 2016.
[URL] [BIB]
Fast adaptive algorithms for optimal feature extraction from Gaussian data.
Youness Aliyari Ghassabeh, Frank Rudzicz, and Hamid Abrishami Moghaddam.
Pattern Recognition Letters, 70:73--79, 2016.
[URL] [BIB]
Random item generation is affected by age.
Namita Multani, Frank Rudzicz, Wing Yiu Stephanie Wong, Aravind Kumar Namasivayam, and Pascal van Lieshout.
Journal of Speech, Language, and Hearing Research, 59(5):1172-1178, 2016.
[URL] [BIB]
The mean shift algorithm and its relation to kernel regression.
Youness Aliyari Ghassabeh and Frank Rudzicz.
Information Sciences, 348:198--208, 2016.
[URL] [BIB]
Acoustic-articulatory relationships and inversion in sum-product and deep-belief networks.
Frank Rudzicz, Arvid Frydenlund, Sean Robertson, and Patricia Thaine.
Speech Communication, 79:61--73, 2016.
[URL] [BIB]
Perspectives on speech and language interaction for daily assistive technology.
Heidi Christensen, Frank Rudzicz, François Portet, and Jan Alexandersson.
ACM Transactions on Accessible Computing (TACCESS), 6(3):1--3, 2015.
[URL] [BIB]
Treatment intensity and childhood apraxia of speech.
Aravind K. Namasivayam, Margit Pukonen, Debra Goshulak, Jennifer Hard, Frank Rudzicz, Toni Rietveld, Ben Maassen, Robert Kroll, and Pascal van Lieshout.
International Journal of Language Communication Disorders, 50(4):529--546, 2015.
[URL] [BIB]
Fast incremental LDA feature extraction.
Youness Aliyari Ghassabeh, Frank Rudzicz, and Hamid Abrishami Moghaddam.
Pattern Recognition, 48(6):1999--2012, 2015.
[URL] [BIB]
Sequential behavior prediction based on hybrid similarity and cross-user activity transfer.
Peng Dai, Shen-Shyang Ho, and Frank Rudzicz.
Knowledge-Based Systems, 77:29--39, 2015.
[URL] [BIB]
Speech interaction with personal assistive robots supporting aging at home for individuals with Alzheimer's disease.
Frank Rudzicz, Rosalie Wang, Momotaz Begum, and Alex Mihailidis.
ACM Transactions on Accessible Computing, 7(2):1--22, 2015.
[URL] [BIB] (invited talk)
2D Psychoacoustic modeling of equivalent masking for automatic speech recognition.
Peng Dai, Frank Rudzicz, Ing Yann Soon, Alex Mihailidis, and Huijun Ding.
Signal Processing, 115:9--19, 2015.
[URL] [BIB]
Incremental algorithm for finding principal curves.
Youness Aliyari Ghassabeh and Frank Rudzicz.
IET Signal Processing, 9(7):521--528, 2015.
[URL] [BIB]
Adjusting dysarthric speech signals to be more intelligible.
Frank Rudzicz.
Computer Speech & Language, 27(6):1163--1177, 2014.
[URL] [BIB]
Acoustic estimation of neck fluid volume.
Azadeh Yadollahi, Frank Rudzicz, Sara Mahallati, Marina Coimbra, and TD Bradley.
Annals of Biomedical Engineering, 42:2132--2142, 2014.
[URL] [BIB]
Noisy source vector quantization using kernel regression.
Youness Aliyari Ghassabeh and Frank Rudzicz.
IEEE Transactions on Communications, 62(11):3825--3834, 2014.
[URL] [BIB]
Using articulatory likelihoods in the recognition of dysarthric speech.
Frank Rudzicz.
Speech Communication, 54(3):430--444, 2012.
[URL] [DATA] [BIB]
The TORGO database of acoustic and articulatory speech from speakers with dysarthria.
Frank Rudzicz, Aravind Kumar Namasivayam, and Talya Wolff.
Language Resources and Evaluation, 46:523--541, 2012.
[URL] [DATA] [BIB]
Vocal tract representation in the recognition of cerebral palsied speech.
Frank Rudzicz, Graeme Hirst, and Pascal van Lieshout.
Journal of Speech, Language, and Hearing Research (JSLHR), 55(4):1190--1207, 2012.
[URL] [DATA] [BIB]
Articulatory knowledge in the recognition of dysarthric speech.
Frank Rudzicz.
IEEE Transactions on Audio, Speech, and Language Processing (TASLP), 19(4):947--960, 2011.
[URL] [DATA] [BIB]

Refereed conferences and workshops

Self-supervised embeddings for detecting individual symptoms of depression.
Sri Harsha Dumpala, Katerina Dikaios, Abraham Nunes, Frank Rudzicz, Rudolf Uher, and Sageev Oore.
Interspeech, 2024.
[BIB]
Developing multi-disorder voice protocols: a team science approach involving clinical expertise, bio-ethics, standards and DEI.
Yael Bensoussan, Satrajit Ghosh, Anais Rameau, Micah Boyer, Ruth Bahr, Stephanie Watts, Frank Rudzicz, Don Bolser, Jordan Lerner-Ellis, Shaheen Awan, Maria Powell, Jean-Christophe Belisle-Pipon, Vardit Ravitsky, Alistair Johnson, Alexandros Sigaras, Olivier Elemento, David Dorr, and Philip Payne.
Interspeech, 2024.
[BIB]
Whister: Using Whisper’s representations for stuttering detection.
Vrushank Changawala and Frank Rudzicz.
Interspeech, 2024.
[BIB]
Long-form evaluation of model editing.
Domenic Rosati, Robie Gonzales, Jinkun Chen, Xuemin Yu, Yahya Kayani, Frank Rudzicz, and Hassan Sajjad.
NAACL, 2024.
[BIB]
Multi-stage retrieve and re-rank model for automatic medical coding recommendation.
Xindi Wang, Robert Mercer, and Frank Rudzicz.
NAACL, 2024.
[BIB]
Auxiliary knowledge-induced learning for automatic multi-label medical document classification.
Xindi Wang, Robert E. Mercer, and Frank Rudzicz.
LREC-COLING, 2024.
[BIB]
Plug and play with prompts: a prompt tuning approach for controlling text generation.
Rohan Deepak Ajwani, Zining Zhu, Jonathan Rose, and Frank Rudzicz.
DAI at AAAI24, 2024.
[URL] [BIB]
Refinerf: modelling dynamic neural radiance fields with inconsistent or missing camera parameters.
Shuja Khalid and Frank Rudzicz.
WACV, 2024.
[BIB]
A state-vector framework for dataset effects.
Esmat Sahak, Zining Zhu, and Frank Rudzicz.
EMNLP, 2023.
[BIB]
Natural language processing for stroke diagnostic imaging characterization.
Brian Bursic, Andrew Cao, Jinyue Feng, Fahad Razak, Amol Verma, MPhil, Moira Kapral, Frank Rudzicz, and Amy YX Yu.
Machine Learning for Healthcare 2023, 2023.
[URL] [BIB]
Investigating the learning behaviour of in-context learning: a comparison with supervised learning.
Xindi Wang, Yufei Wang, Can Xu, Xiubo Geng, Bowen Zhang, Chongyang Tao, Frank Rudzicz, Robert E. Mercer, and Daxin Jiang.
ECAI, 2023.
[URL] [BIB]
A state-vector framework for dataset effects.
Esmat Sahak, Zining Zhu, and Frank Rudzicz.
SRW at ACL 2023, 2023.
[BIB]
Who needs context? classical techniques for alzheimer’s disease detection.
Behrad Taghibeyglou and Frank Rudzicz.
ClinicalNLP, 2023.
[BIB]
Situated natural language explanations.
Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, and Bing Yin.
Natural Language Reasoning and Structured Explanations (NLRSE@ACL 2023), 2023.
[BIB]
Improving automatic quotation attribution in literary novels.
Krishnapriya Vishnubhotla, Frank Rudzicz, Graeme Hirst, and Adam Hammond.
ACL, 2023.
[URL] [BIB]
Predicting fine-tuning performance with probing.
Zining Zhu, Soroosh Shahtalebi, and Frank Rudzicz.
EMNLP, 2022.
[BIB]
Data-driven approach to differentiating between depression and dementia from noisy speech and language data.
Malikeh Ehghaghi, Frank Rudzicz, and Jekaterina Novikova.
Proceedings of W-NUT 2022 at COLING 2022, 2022.
[URL] [BIB]
OOD-Probe: A Neural Interpretation of Out-of-Domain Generalization.
Z Zhu, S Shahtalebi, and F Rudzicz.
SCIS at ICML 2022, 2022.
[URL] [BIB]
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations.
A Balagopalan, H Zhang, K Hamidieh, T Hartvigsen, F Rudzicz, and M Ghassemi.
FAccT22, 2022.
[BIB]
MeSHup: Corpus for Full Text Biomedical Document Indexing.
X Wang, RE Mercer, and F Rudzicz.
LREC, 2022.
[BIB]
Predicting Fine-Tuning Performance with Probing.
Z Zhu, S Shahtalebi, and F Rudzicz.
BigScience at ACL, 2022.
[BIB]
Detoxifying Language Models with a Toxic Corpus.
Y Park and F Rudzicz.
LT-EDI at ACL, 2022.
[BIB]
Relevance in Dialogue: Is Less More? An Empirical Comparison of Existing Metrics, and a Novel Simple Metric.
I Berlot-Attwell and F Rudzicz.
ConvAI at ACL, 2022.
[URL] [BIB]
Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI Evaluation.
H Ngai and F Rudzicz.
BioNLP, 2022.
[BIB]
On the data requirements of probing.
Z Zhu, J Wang, B Li, and F Rudzicz.
Findings of the ACL, 2022.
[BIB]
Neural reality of argument structure constructions.
B Li, Z Zhu, G Thomas, F Rudzicz, and Y Xu.
ACL, 2022.
[BIB]
KenMeSH: Knowledge-enhanced End-to-end Biomedical Text Labelling.
X Wang, B Mercer, and F Rudzicz.
ACL, 2022.
[BIB]
Meth: A remedy for distributional shifts through domain translation.
J-C Gagnon-Audet, S Shahtalebi, F Rudzicz, and I Rish.
ICASSP, 2022.
[BIB]
Language Modelling via Learning to Rank.
A Frydenlund, G Singh, and F Rudzicz.
AAAI, 2022.
[URL] [BIB]
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation.
J Wang, K-C Wang, F Rudzicz, and M Brudno.
NeurIPS, 2021.
[URL] [BIB]
An unsupervised framework for tracing textual sources of moral change.
A Ramezani, Z Zhu, F Rudzicz, and Y Xu.
EMNLP, 2021.
[URL] [BIB]
Intraoperative Adverse Event Detection in Laparoscopic Surgery: Stabilized Multi-Stage Temporal Convolutional Network with Focal-Uncertainty Loss.
H Wei, F Rudzicz, D Fleet, T Grantcharov, and B Taati.
Machine Learning for Healthcare (MLHC2021), 2021.
[URL] [BIB]
An Evaluation of Disentangled Representation Learning for Texts.
KP Vishnubhotla, G Hirst, and F Rudzicz.
Findings of the ACL, 2021.
[URL] [BIB]
How is BERT surprised? Layerwise detection of linguistic anomalies.
B Li, Z Zhu, G Thomas, Y Xu, and F Rudzicz.
ACL-IJCNLP 2021, 2021.
[URL] [BIB]
TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction.
B Li and F Rudzicz.
CMCL at NAACL21, 2021.
[URL] [BIB] Best student paper award
Coughwatch: Real-world cough detection using smartwatches.
D Liaqat, S Liaqat, JL Chen, T Sedaghat, M Gabel, F Rudzicz, and E de Lara.
ICASSP 2021, 2021.
[URL] [BIB]
Opening a Can of Words: Train-Test Overlaps in Clinical Natural Language Processing Datasets.
A Balagopalan, T Naumann, F Rudzicz, and M Ghassemi.
ML4H 2020, 2020.
[BIB]
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP.
J Chen, I Berlot-Attwell, X Wang, S Hossain, and F Rudzicz.
ClinicalNLP at EMNLP2020, 2020.
[URL] [BIB] Best paper award
Examining the rhetorical capacities of neural language models.
Z Zhu, C Pan, M Abdalla, and F Rudzicz.
BlackboxNLP workshop at EMNLP 2020, 2020.
[URL] [BIB]
On Losses for Modern Language Models.
S Aroca-Ouellette and F Rudzicz.
EMNLP, 2020.
[URL] [BIB]
Explainable Clinical Decision Support from Text.
J Feng, C Shaib, and F Rudzicz.
EMNLP, 2020.
[URL] [BIB]
Word class flexibility: A deep contextualized approach.
B Li, G Thomas, Y Xu, and F Rudzicz.
EMNLP, 2020.
[URL] [BIB]
An information theoretic view on selecting linguistic probes.
Z Zhu and F Rudzicz.
EMNLP, 2020.
[URL] [BIB]
Speaker attribution with voice profiles by graph-based semi-supervised learning.
J Wang, X Xiao, J Wu, R Ramamurthy, F Rudzicz, and M Brudno.
INTERSPEECH, 2020.
[URL] [BIB]
To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection.
A Balagopalan, B Eyre, F Rudzicz, and J Novikova.
INTERSPEECH, 2020.
[URL] [BIB]
Sequential Explanations with Mental Model-Based Policies.
AYS Yeung, S Joshi, JJ Williams, and F Rudzicz.
ICML 2020 Workshop on Human Interpretability in Machine Learning (WHI), 2020.
[URL] [BIB]
Representation Learning for Discovering Phonemic Tone Contours.
B Li, JY Xie, and F Rudzicz.
SIGMORPHON at ACL 2020, 2020.
[URL] [BIB]
Identification of primary and collateral tracks in stuttered speech.
R Riad, Bachoud-Lévi, F Rudzicz, and E Dupoux.
LREC, 2020.
[URL] [BIB]
Speaker diarization with session-level speaker embedding refinement using graph neural networks.
J Wang, X Xiao, J Wu, R Ramamurthy, F Rudzicz, and M Brudno.
ICASSP2020, 2020.
[URL] [BIB]
Natural Language Processing with Wearables in Healthcare: Opportunities, challenges, and considerations.
F Rudzicz, R Ng, R Wu, G Carenini, K Ho, and M Abdalla.
eTELEMED2020, March, 2020.
[URL] [BIB] Best paper award
Extracting relevant information from physician-patient dialogues for automated clinical note taking.
S Jeblee, FK Khattak, N Crampton, M Mamdani, and F Rudzicz.
LOUHI 2019: The Tenth International Workshop on Health Text Mining and Information Analysis, November, 2019.
[URL] [BIB]
WearBreathing: Real World Respiratory Rate Monitoring Using Smartwatches.
D Liaqat, M Abdalla, P Abed-Esfahani, M Gabel, T Son, R Wu, A Gershon, F Rudzicz, and E De Lara.
ACM conference on Interactive, Mobile, Wearable and Ubiquitous Technologies 3(2), June, 2019.
[URL] [BIB]
Generative Adversarial Networks for text using word2vec intermediaries.
A Budhkar, K Vishnubhotla, S Hossain, and F Rudzicz.
The 4th Workshop on Representation Learning for NLP (RepL4NLP) at ACL 2019, 2019.
[URL] [BIB]
How do we feel when a robot dies? Emotions expressed on Twitter before and after hitchBOT's destruction.
KC Fraser, F Zeller, D Harris-Smith, S Mohammad, and F Rudzicz.
The 10th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA 2019), 2019.
[URL] [BIB]
Predicting ICU transfers using text messages between nurses and doctors.
FK Khattak, C Pou-Prom, R Wu, and F Rudzicz.
ClinicalNLP 2019, 2019.
[URL] [BIB]
AutoScribe: Extracting clinically pertinent information from patient-clinician dialogues.
FK Khattak, S Jeblee, N Crampton, M Mamdani, and F Rudzicz.
MedInfo, 2019.
[URL] [BIB]
Detecting cognitive impairments by agreeing on interpretations of linguistic features.
Z Zhu, J Novikova, and F Rudzicz.
NAACL., 2019.
[URL] [BIB]
Multilingual prediction of Alzheimer's disease through domain adaptation and concept-based language modelling.
KC Fraser, N Linz, B Li, KL Fors, F Rudzicz, A Konig, J Alexandersson, P Robert, and D Kokkinakis.
NAACL., 2019.
[URL] [BIB]
Detecting dementia in Mandarin Chinese using transfer learning from a parallel corpus.
B Li, Y-T Hsu, and F Rudzicz.
NAACL, 2019.
[URL] [BIB]
Augmenting word2vec with latent Dirichlet allocation within a clinical application.
A Budhkar and F Rudzicz.
NAACL, 2019.
[URL] [BIB]
Centroid-based deep metric learning for speaker recognition.
J Wang, KC Wang, MT Law, F Rudzicz, and M Brudno.
ICASSP, 2019.
[URL] [BIB]
Towards international standards for evaluating machine learning.
F Rudzicz, PA Paprica, and M Janczarski.
SafeAI at AAAI19., 2019.
[URL] [BIB]
Multi-lingual ICD-10 Coding using an Ensemble of Recurrent and Convolutional Neural Networks.
S Jeblee, A Budhkar, S Milic, J Pinto, C Pou-Prom, K Vishnubhotla, G Hirst, and F Rudzicz.
CLEF 2018 eHealth Task 1., 2018.
[URL] [BIB]
Semi-supervised classification by reaching consensus among modalities,.
Z Zhu, J Novikova, and F Rudzicz.
IRASL at NeurIPS., 2018.
[BIB]
The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech.
A Balagopalan, J Novikova, F Rudzicz, and M Ghassemi.
ML4H at NeurIPS., 2018.
[URL] [BIB]
Robustness against the channel effect in pathological voice detection.
Y-T Hsu, Z Zhu, C-T Wang, S-H Fang, F Rudzicz, and Y Tsao.
ML4H at NeurIPS., 2018.
[URL] [BIB]
Learning multiview embeddings for assessing dementia.
C Pou-Prom and F Rudzicz.
EMNLP 2018., 2018.
[URL] [BIB]
A Textual Analysis of U.S. Corporate Social Responsibility Reports.
P Clarkson, J Ponn, G Richardson, F Rudzicz, A Tsang, and J Wang.
2018 Canadian Academic Accounting Association (CAAA) Annual Conference., 2018.
[URL] [BIB]
Interactive Search through Iterative Refinement.
M Wambua, S Raimondo, J Boger, J Polgar, H Chinaei, and F Rudzicz.
2nd International Workshop on Conversational Approaches to Information Retrieval (CAIR'18) at SIGIR 2018, 12 July, Ann Arbor Michigan, USA, 2018.
[URL] [BIB]
Challenges with Real-World Smartwatch based Audio Monitoring.
D Liaqat, R Wu, A Gershon, H Alshaer, F Rudzicz, and E de Lara.
WearSys’18: 4th ACM Workshop on wearable systems and applications, June 10, 2018, Munich, Germany., 2018.
[URL] [BIB]
Speech in Smartwatch based Audio.
D Liaqat, R Wu, A Gershon, H Alshaer, F Rudzicz, and E de Lara.
MobiSys ’18: The 16th Annual International Conference on Mobile Systems, Applications, and Services, June 10–15, 2018, Munich, Germany., 2018.
[URL] [BIB]
Reality Recalled: Elders, Memory and VR, .
MJ Ladly, T Bakker, K Chadha, G Farrelly, K Micak, G Penn, and F Rudzicz.
Proceedings of the 2018 IEEE International Conference on Virtual Systems and Multimedia (VSMM)., 2018.
[BIB]
Touch-Supported Voice Recording to Facilitate Forced Alignment of Text and Speech in an E-Reading Interface, .
RB Axtell, C Munteanu, CD Epp, F Rudzicz, and Y Aly.
Proceedings of the 2018 ACM International Conference on Intelligent User Interfaces., 2018.
[BIB]
On the importance of normative data in speech-based assessment.
Z Noorian, C Pou-Prom, and F Rudzicz.
ML4H, Machine Learning for Health Workshop at NIPS 2017., 2017.
[URL] [BIB]
Detecting Anxiety through Reddit.
JH Shen and F Rudzicz.
Proceedings of CLPsych at ACL2017, 2017.
[URL] [BIB]
On the impact of non-modal phonation on phonological features.
M Cernak, E Noeth, F Rudzicz, H Christensen, JR Orozco-Arroyave, R Arora, T Bocklet, H Chinaei, J Hannink, PS Nidadavolu, JC Vasquez, M Yancheva, A Vann, and N Vogler.
Proceedings of ICASSP 2017, 2017.
[URL] [BIB]
Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease.
JC Vasquez-Correa, JR Orozco-Arroyave, R Arora, E Noeth, N Dehak, H Christensen, F Rudzicz, T Bocklet, M Cernak, H Chinaei, J Hannick, PS Nidadavolu, M Yancheva, A Vann, and N Vogler.
Proceedings of ICASSP 2017, 2017.
[URL] [BIB]
Combining word prediction and r-ary Huffman coding for text entry.
SW Kim and F Rudzicz.
Proceedings of the Seventh Workshop on Speech and Language Processing for Assistive Technologies (SLPAT2016) at Interspeech 2016., 2016.
[URL] [BIB]
CloudCAST - Remote speech technology for speech professionals.
P Green, R Marxer, S Cunningham, H Christensen, F Rudzicz, M Yancheva, A Coy, M Malavasi, L Desideri, and F Tamburini.
Proceedings of Interspeech 2016., 2016.
[URL] [BIB]
Speech recognition in Alzheimer's disease and in its assessment.
L Zhou, K Fraser, and F Rudzicz.
Proceedings of Interspeech 2016., 2016.
[URL] [BIB]
Vector-space topic models for detecting Alzheimer's disease.
M Yancheva and F Rudzicz.
Proceedings of the annual meeting of the Association for Computational Linguistics (ACL16)., 2016.
[URL] [BIB]
Snoring Sound Detection from Respiratory Signal.
M Shokrollahi, S Saha, PH Mohammadabadi, F Rudzicz, and A Yadollahi.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society., 2016.
[URL] [BIB]
Detecting late-life depression in Alzheimer's disease through analysis of speech and language.
K Fraser, F Rudzicz, and G Hirst.
Proceedings of the Third Computational Linguistics and Clinical Psychology Workshop (CLPsych) at NAACL., 2016.
[URL] [BIB]
Remote speech technology for speech professionals - the CloudCAST initiative.
P Green, R Marxer, S Cunningham, H Christensen, F Rudzicz, M Yancheva, A Coy, M Malavasi, and L Desideri.
Proceedings of the 6th Workshop on Speech and Language Processing for Assistive Technologies at Interspeech 2015., 2015.
[URL] [BIB]
Automatic dysfluency detection in dysarthric speech using deep belief networks.
S Oue, R Marxer, and F Rudzicz.
Proceedings of the 6th Workshop on Speech and Language Processing for Assistive Technologies at Interspeech 2015., 2015.
[URL] [BIB]
Using linguistic features longitudinally to predict clinical scores for Alzheimer's disease and related dementias.
M Yancheva, K Fraser, and F Rudzicz.
Proceedings of the 6th Workshop on Speech and Language Processing for Assistive Technologies at Interspeech 2015., 2015.
[URL] [BIB]
Lateralization in emotional speech perception following transcranial direct current stimulation.
A Francois-Nienaber, JA Meltzer, and F Rudzicz.
Proceedings of Interspeech 2015., 2015.
[URL] [BIB]
Automatic identification of received language in MEG.
E Parisotto, YA Ghassabeh, MJ MacDonald, A Cozma, EW Pang, and F Rudzicz.
Proceedings of Interspeech 2015., 2015.
[URL] [BIB]
Social media in human-robot-interaction.
F Zeller, D Harris Smith, JA Duong, M Alanna, E Bagheri, and F Rudzicz.
Proceedings of the 2015 International Conference on Social Media & Society., 2015.
[URL] [BIB]
Emotional affect estimation using video and EEG data in deep neural networks.
A Frydenlund and F Rudzicz.
Proceedings of Canadian AI 2015., 2015.
[URL] [BIB]
EEG dimensionality reduction in automatic identification of synonymy.
E Parisotto, YA Ghassabeh, S Freydoonnejad, and F Rudzicz.
In Proceedings of ICASSP 2015., 2015.
[URL] [BIB]
Classifying phonological categories in imagined and articulated speech.
S Zhao and F Rudzicz.
Proceedings of ICASSP 2015, 2015.
[URL] [BIB] DATA
Combining different modalities in classifying phonological categories.
S Zhao and F Rudzicz.
Proceedings of MLINI2014, NIPS workshop on machine learning and interpretation in neuroimaging, Montreal Canada., 2014.
[URL] [BIB]
Automatically identifying trouble-indicating speech behaviors in Alzheimer's disease.
F Rudzicz, L Chan-Currie, A Danks, T Mehta, and S Zhao.
Proceedings of ACM ASSETS, Rochester NY., 2014.
[URL] [BIB]
Speech recognition in Alzheimer's disease with personal assistive robots.
F Rudzicz, R Wang, M Begum, and A Mihailidis.
Proceedings of the Fifth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT2014) at the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), 26 June, Baltimore USA., 2014.
[URL] [BIB]
Automatic detection of expressed emotion in Parkinson's disease.
S Zhao, F Rudzicz, LG Carvalho, C Márquez-Chin, and S Livingstone.
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP14), 4-9 May, Firenze Italy., 2014.
[URL] [BIB]
Subject independent identification of breath sounds components using multiple classifiers.
H Alshaer, A Pandya, TD Bradley, and F Rudzicz.
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP14), 4--9 May, Firenze Italy., 2014.
[URL] [BIB]
Using text and acoustic features to diagnose progressive aphasia and its subtypes.
K Fraser, F Rudzicz, and E Rochon.
Proceedings of Interspeech, 2013.
[URL] [BIB] ISCA Best Student Paper award
Automatic speech recognition in the diagnosis of primary progressive aphasia.
K Fraser, F Rudzicz, N Graham, and E Rochon.
Proceedings of the Fourth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT2013), 21-22 August, Grenoble France., 2013.
[URL] [BIB]
Automatic detection of deception in child-produced speech using syntactic complexity features.
M Yancheva and F Rudzicz.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), 4-9 August, Sofia Bulgaria., 2013.
[URL] [BIB]
Variations in respiratory sounds in relation to fluid accumulation in the upper airways.
A Yadollahi, F Rudzicz, A Montazeri, and TD Bradley.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 3-7 July, Osaka Japan., 2013.
[URL] [BIB]
Classification of vibratory patterns of the upper airway during sleep.
H Alshaer, F Rudzicz, TH Falk, W-H Tseng, and TD Bradley.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 3-7 July, Osaka Japan., 2013.
[URL] [BIB]
Perceptually induced speech motor representations.
C Neufeld, R Craioveanu, F Rudzicz, W Wong, and P Van Lieshout.
Proceedings of the International Symposium on Imitation and Convergence in Speech, 3-5 September, Aix-en-Provence France., 2012.
[URL] [BIB]
Whole-word recognition from articulatory movements for silent speech interfaces.
J Wang, A Samal, JR Green, and F Rudzicz.
Proceedings of Interspeech 2012, September 9-13, Portland Oregon., 2012.
[URL] [BIB]
Communication strategies for a computerized caregiver for individuals with Alzheimer's disease.
F Rudzicz, R Wilson, A Mihailidis, E Rochon, and C Leonard.
Proceedings of the Third Workshop on Speech and Language Processing for Assistive Technologies (SLPAT2012) at the 13th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2012), 8 June, Montreal Canada., 2012.
[URL] [BIB]
Sentence recognition from articulatory movements for silent speech interfaces.
J Wang, A Samal, JR Green, and F Rudzicz.
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP12), March 25-30, Kyoto, Japan., 2012.
[URL] [BIB]
Using acoustic measures to predict automatic speech recognition performance for dysarthric speakers.
K Mengistu, F Rudzicz, and T Falk.
Proceedings of the 7th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications at INTERSPEECH 2011, August, Firenze Italy., 2011.
[URL] [BIB]
Acoustic transformations to improve the intelligibility of dysarthric speech.
F Rudzicz.
Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies (SLPAT2011) at the ACL Conference on Empirical Methods in Natural Language Processing (EMNLP2011), 30 July, Edinburgh Scotland. , 2011.
[URL] [BIB]
Voice onset self-monitoring and evaluation skills in persons who stutter.
AK Namasivayam, P Van Lieshout, R Kroll, J Le, and F Rudzicz.
Proceedings of the 2011 International Speech Production Seminar (ISSP11), June 20-23, Montreal Canada., 2011.
[BIB]
Comparing humans and automatic speech recognition systems in recognizing dysarthric speech.
KT Mengistu and F Rudzicz.
Proceedings of the Canadian Conference on Artificial Intelligence, May 25-27, St. John's Canada., 2011.
[URL] [BIB]
Adapting acoustic and lexical models to dysarthric speech.
KT Mengistu and F Rudzicz.
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP11), May 22--27, Prague, Czech Republic., 2011.
[URL] [BIB]
Learning mixed acoustic/articulatory models for disabled speech.
F Rudzicz.
Proceedings of the Workshop on Machine Learning for Assistive Technologies at the twenty-fourth annual conference on Neural Information Processing Systems (NIPS 2010), pages 70-78, December, Whistler, British Columbia., 2010.
[URL] [BIB]
Identifying articulatory goals from kinematic data using principal differential analysis.
M Reimer and F Rudzicz.
Proceedings of Interspeech 2010, pages 1608-1611, September 26-30, Makuhari Japan., 2010.
[URL] [BIB]
Correcting errors in speech recognition with articulatory dynamics.
F Rudzicz.
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), pages 60--68, July 11-16, Uppsala Sweden., 2010.
[URL] [BIB]
Towards a noisy-channel model of dysarthria in speech recognition.
F Rudzicz.
Proceedings of the First Workshop on Speech and Language Processing for Assistive Technologies (SLPAT) at the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2010), June 2-6, Los Angeles California, pages 80-88., 2010.
[URL] [BIB]
Adaptive kernel canonical correlation analysis for estimation of task dynamics from acoustics,.
F Rudzicz.
Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'10), March 14-19, Dallas, Texas., 2010.
[BIB]
Summarizing multiple spoken documents: finding evidence from untranscribed audio.
X Zhu, G Penn, and F Rudzicz.
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, August 2009, pp. 549-557, Suntec, Singapore., 2009.
[URL] [BIB]
Applying discretized articulatory knowledge to dysarthric speech.
F Rudzicz.
Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'09), April 19-24, Taipei, Taiwan., 2009.
[URL] [BIB]
Phonological features in discriminative classification of dysarthric speech.
F Rudzicz.
Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'09), April 19-24, Taipei, Taiwan., 2009.
[URL] [BIB]
Towards a Comparative Database of Dysarthric Articulation.
F Rudzicz, P Van Lieshout, G Hirst, G Penn, F Shein, and T Wolff.
Proceedings of the International Speech Production Seminar (ISSP08), December 8-12, Strasbourg France., 2008.
[URL] [BIB]
A critical assessment of spoken utterance retrieval through approximate lattice representations.
S Kazemian, F Rudzicz, G Penn, and C Munteanu.
Proceedings of the ACM International Conference on Multimedia Information Retrieval (MIR2008), October 30-31, Vancouver Canada., 2008.
[URL] [BIB]
Comparing speaker-dependent and speaker-adaptive acoustic models for recognizing dysarthric speech.
F Rudzicz.
Proceedings of Ninth International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '07), October 15-17 2007, Tempe USA., 2007.
[URL] [BIB]
Clavius: Bi-directional parsing for generic multimodal interaction.
F Rudzicz.
Proceedings of COLING-ACL 2006, July 17-21 2006, Sydney Australia., 2006.
[URL] [BIB]
Put a grammar here: Bi-directional parsing in multimodal interaction.
F Rudzicz.
Proceedings of the CHI 2006 Extended Abstracts, Montréal, Québec., 2006.
[URL] [BIB]
The modellers' apprentice - the toolglass metaphor in an immersive environment.
François Rioux, Frank Rudzicz, and Mike Wozniewski.
Proceedings of the 18th British HCI Group Annual Conference, Leeds UK, 2004.
[BIB]
A framework for 3D visualisation and manipulation in an immersive space using an untethered bimanual gestural interface.
Y Boussemart, F Rioux, F Rudzicz, M Wozniewski, and J Cooperstock.
Proceedings of the ACM Symposium on Virtual Reality Software and Technology, Hong Kong., 2004.
[URL] [BIB]
Palettes transparentes hybrides appliquées aux environnements immersifs,.
F Rioux, F Rudzicz, and M Wozniewski.
Proceedings of the 16th Conférence Francophone sur l'Interaction Homme-Machine, Namur, Belgium., 2004.
[BIB]
Using knowledge-poor coreference resolution for text summarization.
Sabine Bergler, Rene Witte, Michelle Khalife, Zhuoyan Li, and Frank Rudzicz.
Proceedings of HLT-NAACL 2003 Text Summarization Workshop (DUC 03), Edmonton Alberta, May, 2003.
[URL] [BIB]

Other

Immunization against harmful fine-tuning attacks.
Domenic Rosati, Jan Wehner, Kai Williams, Łukasz Bartoszcze, Jan Batzner, Hassan Sajjad, and Frank Rudzicz.
arXiv, 2024.
[URL] [BIB]
Llm-generated black-box explanations can be adversarially helpful.
Rohan Ajwani, Shashidhar Reddy Javaji, Frank Rudzicz, and Zining Zhu.
arXiv, 2024.
[URL] [BIB]
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models.
Raeid Saqur, Anastasis Kratsios, Florian Krach, Yannick Limmer, Jacob-Junqi Tian, John Willes, Blanka Horvath, and Frank Rudzicz.
SSRN, 2024.
[URL] [BIB]
Situated natural language explanations.
Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, and Bing Yin.
arXiv, 2023.
[URL] [BIB]
Measuring information in text explanations.
Zining Zhu and Frank Rudzicz.
arXiv, 2023.
[URL] [BIB]
Setting the tone for team performance in the operating room: a constructivist grounded theory study.
Hillary Lia, Melanie Hammond Mobilio, Frank Rudzicz, and Carol-anne Moulton.
16th International Workshop on Behavioural Science Applied to Surgery, 2022.
[BIB]
Reward learning using structural motifs in inverse reinforcement learning.
Raeid Saqur, Animesh Garg, and Frank Rudzicz.
arXiv, 2022.
[URL] [BIB]
Quantifying the task-specific information in text-based classifications.
Z Zhu, A Balagopalan, M Ghassemi, and F Rudzicz.
arXiv:2110.06961, 2021.
[URL] [BIB]
Language modelling via learning to rank.
A Frydenlund, G Singh, and F Rudzicz.
arXiv:2110.06961, 2021.
[URL] [BIB]
What do writing features tell us about ai papers?
Z Zhu, B Li, Y Xu, and F Rudzicz.
arXiv:2107.06310, 2021.
[URL] [BIB]
On the use of linguistic features for the evaluation of generative dialogue systems.
I Berlot-Attwell and F Rudzicz.
arXiv:2104.06335, 2021.
[URL] [BIB]
Challenges for reinforcement learning in healthcare.
E Riachi, M Mamdani, M Fralick, and F Rudzicz.
arXiv:2103:05612, 2021.
[URL] [BIB]
A machine learning approach to chronic obstructive pulmonary disease exacerbation identification and readmission risk quantification.
R Fakhraei, L Kaneswaran, F Rudzicz, A Gershon, and R Wu.
Society of General Internal Medicine Annual Meeting., 2021.
[BIB]
Machine learning forecast of growth in covid-19 confirmed infection cases with non-pharmaceutical interventions and cultural dimensions: algorithm development and validation.
AYS Yeung, F Roewer-Despres, L Rosella, and F Rudzicz.
medRxiv preprint., 2021.
[URL] [BIB]
Semantic coordinates analysis reveals language changes in the ai field.
Z Zhu, Y Xu, and F Rudzicz.
arxiv.org preprint., 2020.
[URL] [BIB]
Task force report on artificial intelligence and emerging digital technologies.
Canada Royal College of Physicians and Surgeons of.
Health Systems and Policy report., 2020.
[URL] [BIB]
The ground truth trade-off in wearable sensing studies.
D Liaqat, R Wu, S Liaqat, E de Lara, A Gershon, and F Rudzicz.
arXiv:2001.09738., 2020.
[BIB]
Using ml to evaluate disorganized speech in schizophrenia.
M Parsapoor, M Lee, C Gabilondo, and F Rudzicz.
2020 Congress of the Schizophrenia International Research Society., 2020.
[BIB]
Talk2me.
Frank Rudzicz.
Database, 2019.
[URL] [BIB] Automated linguistic data collection for personal assessment. 137 participants, 9.6 GB
Generative adversarial networks for text using word2vec intermediaries.
A Budhkar, K Vishnubhotla, S Hossain, and F Rudzicz.
arxiv.org preprint., 2019.
[URL] [BIB]
Deepconsensus: using the consensus of features from multiple layers to attain robust image classification.
Y Li, S Hossain, K Jamali, and F Rudzicz.
arxiv.org preprint., 2018.
[URL] [BIB]
Chaingan: a sequential approach to gans.
S Hossain, K Jamali, Y Li, and F Rudzicz.
arxiv.org preprint., 2018.
[URL] [BIB]
Detecting cognitive impairments by agreeing on interpretations of linguistic features.
Z Zhu, J Novikova, and F Rudzicz.
arxiv.org preprint., 2018.
[URL] [BIB]
Augmenting word2vec with latent dirichlet allocation within a clinical application.
A Budhkar and F Rudzicz.
arxiv.org preprint. Published as [C69], 2018.
[URL] [BIB]
Dropout during inference as a model for neurological degeneration in an image captioning network.
B Li, R Zhang, and F Rudzicz.
arxiv.org preprint., 2018.
[URL] [BIB]
Isolating effects of age with fair representation learning when assessing dementia.
Z Zhu, J Novikova, and F Rudzicz.
arxiv.org preprint., 2018.
[URL] [BIB]
Developing innovative interdisciplinary technological solutions for caregivers of older adults within canada's technology and aging network.
L Demers, J Fast, WB Mortenson, F Routhier, C Auger, S Ahmed, J Boger, F Rudzicz, M Plante, J Eales, and A Pysklywec.
12th ISPRM World Congress, Paris France, 2018.
[URL] [BIB]
Creating the care-rate interface through multi-modal participatory design with caregivers of people with dementia.
P Chauhan, J Boger, T Hussein, S Moon, and J Rudzicz F Polgar.
11th World Conference of the International Society for Gerontechnology (ISG2018), May 7-11, St. Petersburg, FL., 2018.
[BIB]
The impact of design on feelings of trust of online information for family caregivers of people with dementia.
T Hussein, J Boger, and F Rudzicz.
British Computer Society 32nd Human Computer Interaction Conference (BHCI-2018). 2-6 July, Belfast, UK., 2018.
[URL] [BIB]
Finding patterns of events in laparoscopic roux-en-y gastric bypass with machine learning techniques.
L Gordon, F Rudzicz, and T Grantcharov.
Scientific Forum program at the American College of Surgeons., 2018.
[BIB]
Feasibility of using android smartwatches for nearly continuous monitoring of patients with copd.
R Wu, D Liaqat, E de Lara, T Son, F Rudzicz, H Alshaer, P Abed, and A Gershon.
Proceedings of the American Thoracic Society., 2018.
[BIB]
Towards ambulatory cough monitoring using smartwatches.
D Liaqat, R Wu, T Son, A Gershon, H Alshaer, E de Lara, and F Rudzicz.
Proceedings of the American Thoracic Society., 2018.
[BIB]
Early detection of cognitive disorders such as dementia on the basis of speech analysis - a cross-linguistic comparison of speech features.
A Konig, F Rudzicz, KC Fraser, L Kaufman, J Alexandersson, N Linz, J Troger, M Wolters, F Bremond, and P Robert.
Proceedings of AAIC2017., 2017.
[BIB]
Studying neurodegeneration with automated linguistic analysis of speech data.
EA Korcovelos, KC Fraser, J Meltzer, Hirst, G, and F Rudzicz.
Proceedings of AAIC2017., 2017.
[BIB]
Ludwig: a conversational robot for people with alzheimer's.
F Rudzicz, S Raimondo, and C Pou-Prom.
Proceedings of AAIC2017., 2017.
[BIB]
Care-rate: initial development of an artificially intelligent online tool for connecting caregivers to relevant support.
J Boger, F Rudzicz, H Chinaei, K Jónasdóttir, Wambua, M, and J Polgar.
Proceedings of RESNA2017., 2017.
[BIB]
An online resource for caregivers of persons with dementia.
F Rudzicz and J Polgar.
Gerontechnology (ISG2016)., 2016.
[BIB]
Sex, drugs, and violence.
S Raimondo and F Rudzicz.
arxiv.org preprint., 2016.
[URL] [BIB]
Speech interaction with personal assistive robots in the home for people with alzheimer's disease.
F Rudzicz.
Proceedings of the 45th Annual Scientific and Educational Meeting of the CAG., 2016.
[BIB]
Is the progression of neuropsychiatric symptoms similar in early-onset and late-onset alzheimer's disease?
M Multani, F Rudzicz, and MC Tartaglia.
Proceedings of AAIC2016., 2016.
[BIB]
Predicting health inspection results from online restaurant reviews.
S Wong, H Chinaei, and F Rudzicz.
arXiv.org preprint., 2016.
[URL] [BIB]
Sex specific variations in tracheal sound features due to fluid retention in the neck.
M Shokrollahi, F Rudzicz, and A Yadollahi.
Proceedings of the American Thoracic Society, May 2016, San Francisco., 2016.
[BIB]
Kara one.
Frank Rudzicz.
Database, 2015.
[URL] [BIB] Multimodal database of imagined and articulated speech recorded with electroencephalography (EEG), video face tracking, and speech acoustics during phonologically-relevant language tasks. 14 participants, 24 GB.
Learning measures of semi-additive behaviour.
H Chinaei, M Rais-Ghasem, and F Rudzicz.
arXiv.org preprint., 2015.
[URL] [BIB]
Postcard memories: analysis of preliminary usability studies of a mobile postcard application geared towards older adults with early stage dementia of the alzheimer's type.
M Ladly, F Rudzicz, L Wright, Ludlow, BA, A Jofre, C Chen, and K Chadha.
Proceedings of Qualitatives 2015., 2015.
[BIB]
An evidence based care pathway for preschool children with motor speech disorders.
M Pukonen, AK Namasivayam, D Goshulak, F Rudzicz, B Maassen, and PHHM Van Lieshout.
Seminar at the American Speech-Language-Hearing Association Convention, Chicago, USA (November 14-16)., 2013.
[BIB]
Motor speech research study.
AK Namasivayam, R Kroll, M Pukonen, D Goshulak, P Van Lieshout, B Maassen, T Rietveld, and F Rudzicz.
Excellence in Applied Research award from the National Speech-Language & Audiology Canada - National., 2013.
[BIB]
Torgo.
Frank Rudzicz.
Database, 2011.
[URL] [BIB] Acoustic-articulatory database of people with and without dysarthria caused by cerebral palsy. Articulatory data from AG500 electromagnetic articulography. (LDC). 8 participants with dysarthria, 7 without, 18 GB.
T-res: test of rating of emotions in speech: interaction of affective cues expressed in lexical content and prosody of spoken sentences.
BM Ben-David, N Multani, NA-M Durham, F Rudzicz, Lieshout Van, and P.
Proceedings of the 27th Annual Meeting of the International Society for Psychophysics (Fechner Day 2011), pp. 391-396., 2011.
[URL] [BIB]
Production knowledge in the recognition of dysarthric speech.
F Rudzicz.
Doctor of Philosophy, University of Toronto., 2011.
[URL] [BIB]
Clavius: understanding language understanding in multimodal interaction.
F Rudzicz.
Master's of Engineering Thesis, McGill University., 2006.
[URL] [BIB]
Discriminative training of language models in the cmu sphinx framework: experiments and analysis.
F Rudzicz.
Technical report for ECSE-523, Department of Electrical and Computer Engineering, McGill University., 2004.
[BIB]
Alice: a line-based coordinate estimator: towards a more robust soccer robot.
F Rudzicz.
Technical report for ECSE-494, Department of Electrical and Computer Engineering, McGill University., 2003.
[BIB]
Experiments and analysis in cross-document np-coreference.
F Rudzicz.
Honours Thesis, Concordia University., 2003.
[BIB]
Cross-document np coreference: shallow syntactic heuristics vs. probabilistic networks.
F Rudzicz.
Technical Report, CLaC Labs., 2003.
[BIB]
Fuzzy pronominal coreference: two approaches.
F Rudzicz.
Technical Report, CLaC Labs., 2003.
[BIB]
Towards reliable intra-text np-coreference in ers: a practical implementation of a rule-based approach.
F Rudzicz.
Technical report for NSERC USRA., 2002.
[BIB]

Positions

Faculty member - Vector Institute for Artificial Intelligence
Toronto ON - Aug 2017 - present

Associate professor (status) - Department of Computer Science, University of Toronto
Toronto ON - Mar 2018 - present

  • Full member, School of Graduate Studies
  • Associate professor (status), Department of Laboratory Medicine and Pathobiology, University of Toronto
  • Associate member, Institute of Medical Science
  • Associate member, Rehabilitation Sciences Institute (formerly GDRS)
  • Faculty Associate, Centre for Ethics
  • Associate member, School of Graduate and Postdoctoral Studies, Western University
  • Adjunct researcher, College of Health and Medicine, University of Tasmania (2021-2024)
  • Member, Collaborative Program in Neuroscience
  • Member, Toronto Dementia Research Alliance
  • Sessional Lecturer II (early promotion)

Associate professor - Faculty of Computer Science, Dalhousie University
Halifax NS - Sep 2022 - present

  • Director, Advanced Computing CORE Facility
  • Interim Director, Big Data Analytics Institute
  • Advisor, CADTH
  • Associate Scientist, MSSU
  • Member, Connected Minds (CFREF)

Affiliate Scientist - Nova Scotia Health Authority
Halifax NS - Nov 2022 - present

Co-founder - WinterLight Labs
Toronto ON - Jul 2015 - Jan 2023
Acquired by Cambridge Cognition

Advisor - Autumn AI Inc
Toronto ON - Jun 2019 - Feb 2023
Acquired by Qualtrics

Scientist - International Centre for Surgical Safety, Li Ka Shing Knowledge Institute, St Michael's Hospital
Toronto ON - Oct 2018 - Dec 2022

Director of AI - Surgical Safety Technologies Inc
Toronto ON - Oct 2018 - Sep 2022

Assistant professor (status) - Department of Computer Science, University of Toronto
Toronto ON - Sep 2012 - Mar 2018

Scientist - Toronto Rehabilitation Institute, University Health Network
Toronto ON - Sep 2012 - Oct 2018

Founder and CEO - Thotra Incorporated
Toronto ON - Sep 2011 - Aug 2016

Visiting Scholar - Whiting School of Engineering, Johns Hopkins University
Baltimore USA - Jun 2016 - Aug 2016

Research intern - Quillsoft Ltd and Bloorview Kids Rehab
Toronto ON - Jan 2009 - Sep 2009

Research assistant - Centre for Intelligent Machines, McGill University
Montréal QC - Jan 2004 - May 2006

Speech science intern - Scansoft Inc
Boston USA - May 2003 - Aug 2003

Research assistant and system administrator - CLaC Labs, Concordia University
Montréal QC - Jan 2001 - Dec 2003

Speech science intern - SpeechWorks Inc
Montréal QC - Jan 2001 - Aug 2001

Education

PhD - University of Toronto - 2011, June

  • Advisor: Graeme Hirst
  • Title: Production knowledge in the recognition of dysarthric speech

MEng - McGill University - 2006, December

  • Advisor: Jeremy Cooperstock
  • Title: CLAVIUS: Understanding Language Understanding in Multimodal Interaction
  • Member: Centre for Intelligent Machines

BSc - Concordia University - 2003, December

  • Advisor: Sabine Bergler
  • Title: Experiments and Analysis in Cross-Document NP-Coreference
  • Member: Institute for Cooperative Education, CLaC Labs
  • Commendations: Honours, Great Distinction

Teaching

  • CSCI 4144/6405 (Dalhousie) - Data Mining and Warehousing - Instructor - Spring 2024
  • CSCI 4157/6518 (Dalhousie) - Deep Speech Technologies - Instructor - Fall 2023
  • DGIN 5401 (Dalhousie) - Operationalized Machine Learning in Healthcare - Instructor - Fall 2023
  • ACS (American College of Surgeons) - AI and ML: Transforming Surgical Practice and Education - Instructor - online 2023
  • CSCI 4144/6405 (Dalhousie) - Data Mining and Warehousing - Instructor - Spring 2023
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2022
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2021
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2020
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2019
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2018
  • C4M, Computing for Medicine (Toronto) - Natural language processing in clinical medicine - Seminar - Fall 2017
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2017
  • C4M, Computing for Medicine (Toronto) - Natural language processing in clinical medicine - Seminar - Fall 2016
  • CSC 490/2600 (Toronto) - Artificial intelligence in clinical medicine - Instructor - Fall 2016
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2016
  • CSC 485/2501 (Toronto) - Computational Linguistics - Instructor - Fall 2015
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2015
  • CSC 2518 (Toronto) - Spoken Languge Processing - Instructor - Fall 2014
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2014
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2013
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2012
  • CSC 401/2511 (Toronto) - Natural Language Computing - Instructor - Spring 2011
  • CSC 108 (Toronto) - Introduction to Computer Programming - TA - Summer 2010
  • CSC 401 (Toronto) - Natural Language Computing - TA - Spring 2010
  • CSC 401/2511 (Toronto) - Natural Language Computing - TA - Spring 2009
  • CSC 108 (Toronto) - Introduction to Computer Programming - TA - Fall 2008
  • CSC 190 (Toronto) - Computer Algorithms, Data Structures and Languages - TA - Winter 2007
  • ECSE 526 (McGill) - Artificial Intelligence - TA - Winter 2006
  • ECSE 424 (McGill) - Human Computer Interaction - TA - Winter 2006
  • COMP 472 (Concordia) - Artificial Intelligence - TA - Winter 2003
  • COMP 472 (Concordia) - Artificial Intelligence - TA - Fall 2002
  • COMP 472 (Concordia) - Artificial Intelligence - TA - Summer 2002
  • COMP 472 (Concordia) - Artificial Intelligence - TA - Winter 2002

Team

Postdoc

  • Samaneh Hosseini, PDF, 2023-present (with Kelly Lyons at Faculty of Information, University of Toronto )
  • Elham Seifossadat, PDF, 2023-present ( at Tali.AI )
  • Michael Fralick, PDF, 2022-2023 (with Muhammad Mamdani )
  • Daniyal Liaqat, PDF, 2020-2022
  • Soroosh Shahtalebi, PDF, 2021-2022
  • Muhammad Raisul Alam, PDF, 2019-2021 (with Alex Mihailidis )
  • Serena Jeblee, PDF, 2020-2021
  • Shalmali Joshi, PDF, 2018-2020
  • Mahboobeh Parsapoor, PDF, 2019-2020
  • Faiza K Khattak, PDF, 2018-2019, next: Manulife
  • Margot Yann, PDF, 2018-2019 (with Thérèse Stukel )
  • Majid Komeili, PDF, 2017-2018, next: faculty, Carleton University
  • Hamidreza Chinaei, PDF, 2014-2017
  • Zeinab Noorian, PDF, 2017
  • Jennifer Boger, PDF, 2016, next: faculty, University of Waterloo
  • Mehrnaz Shokrollahi, PDF, 2015-2016 (with Azadeh Yadollahi )
  • Youness Aliyari Ghassabeh, PDF, 2014-2015, next: Bank of Montreal
  • Steven Livingstone, PDF, 2014-2015, next: faculty, University of Wisconsin
  • Ricard Marxer, PDF, 2015 (with Phil Green at University of Sheffield )
  • Jana Besser, PDF, 2013-2014, next: Phonak
  • Peng Dai, PDF, 2014 (with Alex Mihailidis ), next: University of Western Ontario

Graduate

  • Joana Amorim, PhD, 2023-present ( at Dalhousie University )
  • Ian Berlot-Attwell, PhD, 2019-present ( at Computer Science, University of Toronto )
  • Ali Dadsetan, PhD, 2023-present ( at Faculty of Computer Science, Dalhousie University )
  • Sagar Devesh, MSc, 2023-present ( at Faculty of Computer Science, Dalhousie University )
  • Shadi Dorosti, MSc, 2023-present (with Jeremy Brown at School of Biomedical Engineering, Dalhousie University )
  • Jinyue Feng, PhD, 2021-present ( at Computer Science, University of Toronto )
  • Arvid Frydenlund, PhD, 2013-present (with Rich Zemel at Computer Science, University of Toronto )
  • Amanjit Kainth, MSc->PhD, 2018-present ( at Computer Science, University of Toronto )
  • Hillary Lia, MD/PhD, 2021-present (with Carol-Anne Moulton at Institute for Medical Sciences, University of Toronto )
  • Ahmad Rezaie Mianroodi, PhD, 2023-present ( at Faculty of Computer Science, Dalhousie University )
  • Yikang Pan, MScAC, 2024-present ( at Boson AI )
  • Joao Pimentel, PhD, 2023-present ( at Dalhousie University )
  • Chang Qu, MScAC, 2024-present ( at Trillium Health Partners )
  • Elahe Rahimi, PhD, 2023-present ( at Faculty of Computer Science, Dalhousie University )
  • Francois Roewer-Despres, MSc->PhD, 2018-present ( at Computer Science, University of Toronto )
  • Domenic Rosati, PhD, 2023-present (with Hassan Sajjad at Faculty of Computer Science, Dalhousie University )
  • Raeid Saqur, PhD, 2019-present ( at Computer Science, University of Toronto )
  • Dorsa Soleymani, MSc, 2023-present ( at Faculty of Computer Science, Dalhousie University )
  • Marina Tawfik, PhD, 2018-present ( at Computer Science, University of Toronto )
  • Qanita Turabi, MSc, 2023-present (with Chistopher Parshuram at Institute for Medical Sciences, University of Toronto )
  • Xijie Zeng, MSc, 2024-present ( at Dalhousie University )
  • Maria Escalante, MScAC, 2024 ( at Q2 )
  • Shuja Khalid, PhD, 2019-2024 ( at Computer Science, University of Toronto ), next: Stanford University
  • Xindi Wang, PhD, 2020-2024 (with Bob Mercer at Western University ), next: Cornell University
  • Zining Zhu, PhD, 2019-2024 ( at Computer Science, University of Toronto ), next: Faculty at Stevens Institute
  • Andy Lee, MScAC, 2023 ( at Centre for Global Health Research )
  • Chanpreet Singh, MACS, 2023 ( at Dalhousie University )
  • Mohamed Abdalla, MSc->PhD, 2016-2022, next: Faculty at University of Alberta
  • Aparna Balagopalan, PhD, 2020-2022 (with Marzyeh Ghassemi at Computer Science, University of Toronto ), next: Massachusetts Institute of Technology
  • Omkar Dige, MScAC, 2022 ( at Microsoft Turing )
  • Ahmad Abdollahpouri Hosseini, MScAC, 2022 ( at Samsung AI Research )
  • Demetres Kostas, MSc->PhD, 2016-2022
  • Bai Li, MSc->PhD, 2017-2022
  • Sayyed Nezhadi, PhD, 2018-2022 (with Sanja Fidler )
  • Hillary Ngai, MSc, 2020-2022, next: Google Brain
  • Yoona Park, MSc, 2020-2022, next: Apple
  • Diljot Singh, MScAC, 2022 ( at ScotiaBank )
  • Ruijing Zeng, MScAC, 2022 ( at Vanguard )
  • Sourav Bhattacharjee, MScAC, 2021 ( at Layer6 )
  • John Chen, MSc, 2019-2021, next: Medical school, McGill University
  • Malikeh Ehghaghi, MScAC, 2021 ( at Winterlight Labs )
  • Yuchen Li, MSc, 2019-2021
  • Guanxiong Liu, MScAC, 2021 ( at Samsung )
  • Kyle Alexander Oppenheimer, MScAC, 2021 ( at Microsoft )
  • Jixuan Wang, PhD, 2017-2021 (with Michael Brudno ), next: Amazon (Alexa)
  • Stephane Aroca-Ouellette, MSc, 2018-2020, next: University of Colorado at Boulder
  • Daniyal Liaqat, PhD, 2016-2020 (with Eyal de Lara )
  • Elsa Riachi, MSc, 2018-2020
  • Arnold Yeung, MSc, 2018-2020, next: TikTok
  • Akshay Budhkar, MSc, 2017-2019, next: Georgian Partners
  • Safwan Hossain, MSc, 2018-2019 (with Nisarg Shah ), next: Harvard University
  • Manasa Bharadwaj, MScAC, 2018 ( at ROSS )
  • Tianyi Chen, MScAC, 2018 ( at RSVP Technologies )
  • Scarlett Jia Guo, MScAC, 2018 ( at Deloitte )
  • Nicole Langballe, MScAC, 2018 ( at ROSS )
  • Antonia Mouawad, MScAC, 2018 ( at ROSS )
  • Yomna Omar, MScAC, 2018 ( at Caseware )
  • Chloe Pou-Prom, MSc, 2016-2018, next: Unity Health Toronto
  • Stefania Raimondo, MSc, 2015-2018, next: ElementAI
  • Simon Rojas, MScAC, 2018 ( at ROSS )
  • Raeid Saqur, MScAC, 2018 ( at Creative Destruction Labs )
  • Siddhartha Thota, MScAC, 2018 ( at ROSS )
  • Muuo Wambua, MSc, 2016-2018 (with Graeme Hirst ), next: Apple
  • Matt Arnold, MScAC, 2017 ( at CaseWare )
  • Cole Boudreau, MScAC, 2017 ( at CaseWare )
  • Willie Chang, MScAC, 2017 ( at Synervoz )
  • Colt Chapin, MScAC, 2017 ( at ROSS )
  • Lee Hao-Wei, MScAC, 2017 ( at ROSS )
  • Mete Kemertas, MScAC, 2017 ( at Tealbook )
  • Rafael Lacerda, MScAC, 2017 ( at ROSS )
  • Simrandeep Singh, MScAC, 2017 ( at ScotiaBank )
  • Eda Doko, MScAC, 2016 ( at Kira Systems )
  • Abraham Escalante, MScAC, 2016 ( at Caseware )
  • Jorge Andres Gomez Garcia, visiting scholar (PhD), 2015-2016 ( at Technical University of Madrid )
  • Syed Rizwan Gilani, MScAC, 2016 ( at Amazon )
  • Alexander Halliwushka, MScAC, 2016 ( at Ubisoft )
  • Thomas LaMantia, MScAC, 2016 ( at Caseware )
  • Maria Yancheva, MSc, 2014-2016, next: Winterlight Labs
  • Liu Yang, MScAC, 2016 ( at Meta )
  • Rachel Twiss, MScAC, 2015
  • Shunan Zhao, MSc, 2013-2015
  • Craig Hagerman, MScAC, 2014 ( at Wattpad )

Undergraduate

  • Robie Gonzales , honours undergraduate thesis, 2024 ( at Dalhousie University )
  • Xinxin Yu, honours undergraduate thesis, 2024 ( at Dalhousie University )
  • Arjun Banga, honours undergraduate thesis, 2023 ( at Dalhousie University )
  • Ramin Fathian, undergraduate summer student, 2023 ( at Vector Institute )
  • Xijie Zeng, honours undergraduate thesis, 2023 ( at Dalhousie University )
  • Jie Zhang, undergraduate course project, 2023 ( at Dalhousie University )
  • Jonathan Zhao, undergraduate summer student, 2023 (with Tina Felfeli at T-CAIREM scholarship )
  • Philipp Eibl, undergraduate course project, 2022, next: University of Southern California
  • Sophie Nam, undergraduate course project, 2022
  • Benjamin Eyre, summer undergrad, undergraduate course project, 2018,2021
  • Lydia Jeong, undergraduate course project, 2021
  • Daniyar Akhmedjanov, undergraduate Engineering Science thesis, 2019-2020
  • Heung Ryeol Cho, undergraduate Engineering Science thesis, 2019-2020
  • Yuvrender Gill, undergraduate course project, 2020
  • Marco Istasy, undergraduate course project, 2020
  • Gary Leung, undergraduate Engineering Science thesis, 2019-2020
  • Philip Lu, undergraduate Engineering Science thesis, 2019-2020
  • Yinqing Luo, undergraduate Engineering Science thesis, 2019-2020
  • Tony Nguyen, undergraduate course project, 2020
  • Chu Pan, undergraduate Engineering Science thesis, 2019-2020, next: Carnegie Mellon University
  • Nuofan Xu, undergraduate Engineering Science thesis, 2019-2020
  • Seung Yang, undergraduate Engineering Science thesis, 2019-2020
  • Kejie Zhao, undergraduate Engineering Science thesis, 2019-2020
  • Christopher Chu, undergraduate thesis, 2018-2019
  • Serdarcan Dilbaz, undergraduate Fulbright scholar, 2019
  • Austin Han, undergraduate course project, 2019
  • Shayan Kousha, undergraduate course projects, 2018-2019
  • Tanuj Kumar, undergraduate course project, 2019
  • Minkang Suk, undergraduate thesis, 2018-2019
  • Jing Yi Xie, undergraduate course project, 2019
  • Zhi Huan Yu, undergraduate course project, 2019
  • Zining Zhu, undergraduate thesis, 2018-2019
  • Ian Berlot-Attwell, undergraduate course project, 2018
  • John Chen, undergraduate summer student, 2018
  • Armand Gurgu, undergraduate course project, 2018
  • Wilson Huang, undergraduate Engineering Science thesis, 2017-2018
  • Kiarash Jamali, summer undergraduate, 2018
  • Yuchen Li, summer undergraduate, 2018
  • Marck Mercado, summer medical undergraduate, 2018
  • Shweta Mogalapalli, undergraduate course project, 2018
  • Stacy Nguyen, summer medical undergraduate, 2018
  • YueLan Qin, summer undergraduate, 2018
  • Taryn Rohringer, summer medical undergraduate, 2018
  • Jin Zhou, undergraduate course project, 2018
  • Kawin Ethayarajh, undergraduate course project, then undergraduate thesis, 2016-2017, next: Stanford University
  • Kevin Hugh, undergraduate course project, 2017
  • Rui Janson, undergraduate Engineering Science thesis, 2016-2017
  • Amanjit Kainth, undergraduate course project, 2017
  • Ellen Korcovelos, undergraduate Fulbright scholar, 2016-2017 (with Graeme Hirst )
  • Judy Han Shen, undergraduate Engineering Science thesis, 2016-2017, next: Massachusetts Institute of Technology (MIT)
  • Viviane Catini, undergraduate Science Without Borders student, 2016
  • Syed Farooq, undergraduate Engineering Science thesis, 2015-2016
  • Chen Ying, Mitacs Globalink summer undergraduate student, 2016
  • Mohamed Abdalla, undergraduate course project, 2015
  • Francisco Canas, undergraduate course project, 2015
  • Oscar Chen, undergraduate NSERC USRA, 2015 (with Sheila McIlraith )
  • Hengwei Guo, undergraduate UTRECS, 2015
  • Seung-Wook Kim, undergraduate course project, 2015
  • Hubert Lin, undergraduate NSERC USRA, 2015 (with Sheila McIlraith ), next: Cornell University
  • Stefania Raimondo, undergraduate Engineering Science thesis, 2014-2015
  • Ealona Shmoel, undergraduate course project, 2015
  • Luke Zhou, NSERC USRA + two undergraduate course projects, 2015
  • Pedram Adibi, undergraduate project, 2014
  • Leila Chan Currie, undergraduate course project, 2014
  • Andrew Danks, undergraduate course project, 2013-2014
  • Siamak Freydoonnejad, undergraduate course project, 2014
  • Tejas Mehta, undergraduate Engineering Science thesis, 2013-2014
  • Emilio Parisotto, undergraduate course project, 2014
  • Rafael Ruggi, undergraduate exchange student, 2014
  • Diego Santos, undergraduate exchange student, 2014
  • Yixin Wang, summer exchange undergraduate student, 2014
  • Giorgia Willits, summer exchange undergraduate student, 2014 ( at UC Berkeley )
  • Cristian Caloian, undergraduate course project, 2013
  • Leonardo Gonzaga Carvalho, undergraduate intern, 2013
  • Alex Chen, undergraduate summer student, 2013 (with Alex Mihailidis )
  • Marina Coimbra, undergraduate intern, 2013
  • Soumendu Majee, Mitacs Globalink summer undergraduate, 2013
  • Jan S. Rudy, undergraduate summer student, 2013
  • Maria Yancheva, undergraduate Engineering Science thesis, 2012-2013
  • Eigo Kawatani, undergraduate course project, 2012 (with Gerald Penn )

Research assistants and associates

  • Brandon Jaipersaud, RA, 2023-2024 ( at Vector Institute )
  • Farshad Tajeddinisarvestani, RA, 2024 ( at Vector Institute )
  • Kristin Huang, RA, 2023 ( at Vector Institute )
  • Behrad Taghibeyglou, RA, 2023 ( at Vector Institute )
  • Rohan Deepak Ajwani, RA, 2022
  • Samin Khan, RA, 2020, next: Stanford University
  • Rachid Riad, visiting scholar, 2018
  • Theresa Ma, RA, 2017
  • Jordan Ponn, RA, 2017
  • Angela Ning Ye, RA, 2017
  • Liam Kaufman, RA, 2015-2016
  • Peyman Hadi, RA, 2014-2015 (with Azadeh Yadollahi )
  • Hoda Zare, RA, 2015
  • Fiona Hobler, RA, 2013-2014
  • Selvana Morcos, RA, 2014
  • Farook Sattar, affiliate scientist, 2014
  • Aman Montazeri, RA, 2012-2013

Committee member

  • Mustafa Haiderbhai, PhD student (committee member), 2021-present (with Sven Dickinson at Computer Science, University of Toronto )
  • Frank Niu, PhD student (committee member), 2021-present (with Gerald Penn at Computer Science, University of Toronto )
  • Maksym Yaranukhin, PhD student (committee member), 2023-present (with Evangelos Milios at Dalhousie University )
  • Jade Yu, PhD student (committee member), 2022-present (with Yang Xu at Computer Science, University of Toronto )
  • Zoey Zuo, PhD student (committee member), 2023-present (with Norman Farb at Psychological Clinical Science, University of Toronto )
  • John Giorgi, PhD student (committee member), 2020-2024 (with Gary Bader and Bo Wang at Computer Science, University of Toronto )
  • Timur H. Latypov, PhD (committee member), 2019-2024 (with Mojgan Hodaie at Institute for Medical Sciences, University of Toronto )
  • Mashrura Tasnim, External examiner, PhD, 2024 ( at Computer Science, University of Alberta )
  • Tiana Wei, PhD student (committee member), 2021-2024 (with Jed Meltzer )
  • Harshit Agarwal, MSc external examiner, 2023 ( at Computer Science, Dalhousie University )
  • Lauren Gordon, PhD student (committee member), 2018-2023 (with Teodor Grantcharov at Surgery, University of Toronto )
  • Kazi Hasan, Internal external examiner, MSc, 2023 ( at Computer Science, Dalhousie University )
  • Sean Robertson, PhD student (committee member), 2017-2023 (with Gerald Penn at Computer Science, University of Toronto )
  • Zhewei Sun, Internal external examiner, PhD, 2023 ( at Computer Science, University of Toronto )
  • Ronit Desai, MSc external examiner, 2022 ( at Computer Science, Dalhousie University )
  • Shilo McBurney, PhD student (committee member), 2018-2022 (with Natasha Crowcroft )
  • Guangyi Zhang, PhD external examiner, 2022 ( at Electrical and Computer Engineering, Queen's University )
  • Christopher Meaney, PhD student (committee member), 2018-2020 (with Michael Escobar )
  • Jingcheng Niu, MSc external examiner, 2020 ( at Computer Science, University of Toronto )
  • Nabiha Asghar, PhD external examiner, 2019 ( at Computer Science, University of Waterloo )
  • Gandharv Anil Patil, MEng external examiner, 2019 ( at Engineering, McGill University )
  • Mansoor Pevaiz, PhD external examiner, 2016-2019 ( at Northeastern University )
  • Anis Sharafoddini, PhD external examiner, 2019 ( at University of Waterloo )
  • Jeanne Sinclair, PhD student (committee member), 2018-2019 (with Eunice Jang )
  • Ryan Visee, MASc student (committee member), 2018-2019 (with Jose Zariffa )
  • Alborz Rezazadeh, PhD student (committee member), 2015-2018 (with Tom Chau ), next: Samsung AI
  • Gagandeep Singh, MSc external examiner, 2018 ( at Computer Science, University of Toronto )
  • Libby Barak, PhD external examiner, 2016 ( at Computer Science, University of Toronto )
  • Kathleen Fraser, PhD student (committee member), 2013-2016 (with Graeme Hirst and Jed Meltzer ), next: National Research Council
  • Yunpeng Li, MI (committee member), 2016 (with Kelly Lyons )
  • Tong Wang, PhD external examiner, 2016 ( at Computer Science, University of Toronto )
  • Kevin Yang, MHSc student (committee member), 2015-2016 (with Teodor Grantcharov )
  • Amanda Chou, MAsc external examiner, 2015 ( at Mechanical and Industrial Engineering, University of Toronto )
  • Vanessa Wei Feng, PhD external examiner, 2014 ( at Computer Science, University of Toronto )
  • Navdeep Jaitly, PhD student (committee member), 2013-2014 (with Geoff Hinton ), next: Google
  • Helia Mohammadi, PhD external examiner, 2014 ( at Electrical and Computer Engineering, University of Toronto )
  • Abdel-Rahman Mohammed, PhD external examiner, 2014 ( at Computer Science, University of Toronto )

Awards

Best Student Paper award
CMCL at NAACL21
2021, International

Best Paper award
ClinicalNLP at EMNLP2020
2020, International

Best Paper award
eTELEMED 2020
2020, International

Connaught Innovation Award
University of Toronto
2018, Institutional, $45,305

Innovation and Science Early Researcher Award
Ontario Ministry of Research
2016, Provincial, $150,000

Winner, pitch competition (with Winterlight Labs)
Aging 2.0
2016, International

Excellence in Applied Research
National Speech-Language & Audiology Canada
2016, National

Research in Print award
Baycrest
2015, Institutional

Best Student Paper Award (Katie Fraser first author, Interspeech 2013)
ISCA
2013, International

Young Network Investigator award
GRAND-NCE
2012, National, $5000

Entrepreneur award
Ontario Brain Institute
2012, Provincial, $50,000

Elevate Industrial Fellowship
MITACS
2011-2012, National, $65,000

Graduate Scholarship
Ontario
2009-2010, Provincial, $15,000

Accelerate Canada award
MITACS
2009, National, $15,000

Canada Graduate Scholarship (Doctoral)
NSERC
2006-2009, National, $105,000

Majors Fellowship
McGill University
2006, Institutional, $30,000

Bourse de Maitrise
FQRNT
2004-2005, Provincial, $25,000

CS graduation award
Concordia University
2004, Institutional, $1,200

undergraduate research award (AI)
NSERC
2002, National, $6,000

Dean's List
Concordia University
2001-2003, Institutional

Grants (selected)

All grants as PI, and in CAD, except where noted.

Next Wave Fund
Dalhousie University
2024-2025, Institutional, $35,000

Stroke in Women: Growing Opportunities to Realize optimal Evaluation, Diagnosis, and outcomes (StrokeGoRed)
Heart & Stroke
2024-2029, National, PI, Amy Yu: NPI, $4,983,959.19

The Role of Limbic Structures, Memory and Emotion in Chronic Neuropathic Pain
CIHR
2024-2029, National, Co-PI, Mogdan Hodai: NPO, $1,400,000

Predicting Readmission Outcomes using Biostatistical Evaluation and Machine Learning (PROBE ML)
Heart & Stroke
2024-2027, National, Co-PI, Douglas Lee: NPI, $276,037

Reducing the impacts of emotion recognition bias on Canadians
SSHRC Insight grant
2024-2029, National, Co-I, Steven Livingstone: PI, $391,972

Enabling Neuroscience research Approaches for Brain, feeLings and Emotions (ENABLE): An Platform for Clinical Trials in Mood Disorders
Health Canada, Ontario Brain Institute, Janssen R&D (CAN-BIND)
2023-2026, National, Co-I, Benicio N. Frey: PI, $5,031,457

Artificial Intelligence Automation to Improve Family Medicine Workflow
T-CAIREM
2023-2024, National, PI, $100,000

Promoting diversity and fairness in narrative text recommendation by disentangled representations
Naver Corporation (Korea)
2022-2027, International, PI, $1,196,160

Voice as a Biomarker of Health: Building an ethically sourced, bioaccoustic database to understand disease like never before
National Institutes of Health (NIH)
2022-2026, International, Co-I, Yael Bensoussan: NPI, $13,817,302 USD

Heart-Brain IMPACT award
Heart and Stroke Foundation and Brain Canada
2022-2026, National, Co-PI, Douglas S Lee: NPI, $2,900,000

ICES UofT Data Access, The Ontario Uveitis Cohort (OUC) Database - Development and validation of an administrative data algorithm
CANSSI Ontario
2021, Provincial, $10,000

An Artificial Intelligence-based MR Imagine Reconstruction Framework
CIFAR-Temerty Innovation Catalyst Grant
2021-2023, Institutional, Co-PI; Mojgan Hodaie:PI, $130,000

Machine Learning Methods in Health
Research program, Unity Health Toronto
2021, Institutional, $50,000

Machine learning in surgical safety
NSERC Discovery
2020-2025, National, $120,000

iSSD@OISE: A Tool for Strengthening the Global Competencies of the OISE International and Domestic Graduate Student Community
International Student Experience Fund, University of Toronto
2020-2023, Institutional, Co-applicant; Eunice Jang:PI, $299,750

Machine learning in the operating room: focus, performance, and the medical record
Mitacs
2020, National, $90,000

Evaluating the impact of COVID-19 pandemic on primary care using real world data: focus mental health
CIHR Operating Grant
2020-2021, National, Co-I; Karen Tu:PI, $200,000

Machine learning in surgical safety
Sponsored research (Electronics and Telecommunications Research Institute, Korea)
2020-2021, International, $115,000

Values Ecosystems in the Design of Artificial Intelligence for Health Care: An Exploratory Focused Ethnography
SSHRC Insights
2020, National, Co-I; James Shaw:PI, $61,000

CovidFree@Home: Development and validation of a multivariable prediction model of deterioration in patients diagnosed with COVID-19 who are managing at home
CIHR COVID-19 Rapid Research
2020, National, Co-I; Andrea S Gershon:PI, $620,133

Computer Science Fellowship
Michael J Fox & Weston Foundation
2019-2020, International, $150,000 USD

Mapping the Equity Dimensions of AI in Public Health
CIHR Planning grant
2019, National, Co-applicant; Maxwell Smith:PI, $39,568

Natural language processing in healthcare data
NSERC Discovery
2019-2020, National, $27,600

Identification of patients admitted with COPD exacerbations and stratification of those at high risk of readmission using natural language processing and machine learning
CIHR/CLA Boehringer Ingelheim Canada COPD Catalyst Grant
2019, National, Co-PI; Robert Wu:PI, $30,000

The benefits of pneumococcal immunization programs for ...
CIRN
2019-2021, National, Co-investigator; PIs: Natasha Crowcroft and Fawziah Lalji, $304,682

Exploiting natural neural control to minimize speech errors among language learners
NSERC Engage (with Syngli Incorporated)
2018, National, $25,000

Explainable AI
Electronics and Telecommunications Research Institute, Korea
2018-2019, International, $196,000

Comprehensive Ontario Microbiology laBoratory Administrative daTa for AntiMicrobial Resistance (COMBAT-AMR)
CIHR Project grant
2018-2021, National, Co-applicant; Kevin Brown:PI, $608,176

Assistive robots for people with dementia
JP Bickell Foundation Research grant
2018, National, $46,640

Digging into Data Challenge
NSERC Discovery Frontiers
2017-2020, National, $100,000

Automatic remote monitoring of cognition through speech
Ontario Centres of Excellence Health Technologies Fund (with WinterLight and Revera)
2017, Provincial, $94,836

Natural Language Computing
Google Cloud Platform Education grant
2017, International, $5000 USD

Assessing cognitive ability using automated assessment of speech
AGE-WELL Catalyst
2017, National, $43,765

System for recording and analyzing telephone conversations between humans and artificial intelligence
NSERC Research Tools & Instruments
2017, National, $16,107

Automatic remote screening of speech features associated with Alzheimer's disease
Canadian Institutes of Health Research (CIHR) and the Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Health Research Projects (CHRP)
2017-2020, National, $648,664

Cognitive assessment through speech
AGE-WELL Strategic Investment Program
2016, National, $24,675

Remote Monitoring of Neurodegeneration through Speech
Johns Hopkins Jelinek Summer Workshop
2016, International, TBD

SmartStart Seed (with Winterlight Labs)
Ontario Centres of Excellence
2016, Provincial, $37,416

Speech-based conversation model for data analytics
NSERC Engage (with IBM)
2015, National, $25,000

A dynamic emotion feedback system for music using audio, symbolic, and physiological features
NSERC Collaborative Research and Development Grant
2015-2017, National, Co-I; Frank Russo:PI, $440,000

CARE-RATE - Online assistive technology rating and recommending system for caregivers
AGE-WELL
2015-2016, National, Co-PI; Jan Polgar:Co-PI, $281,005

Developing a wearable device to record physiological signals during sleep
OCE VIP I (with iDAPT Somno Inc.)
2015, Provincial, $20,000

Automatic assessment of dementia from speech
Banting & Best Centre for Innovation & Entrepreneurship Collaboration Fellowship (with WinterLight)
2015, Institutional, $10,000

Individually optimized brain stimulation in dementia using MEG
Ontario Brain Institute Ontario Neurodegenerative Disease Research Initiative (ONDRI) Basic Science Program
2014-2018, Provincial, Co-PI; Jed Meltzer:PI), $726,655

Software to engage individuals with Alzheimers disease in conversation in support of speech therapy
Alzheimer Society of Canada Young Investigator grant
2014-2017, National, $180,000

A cloud-based computational resource for clinical and educational applications of speech technology
Leverhulme Trust grant
2014-2017, International, Co-I; Phil Green:PI, £124,994

Automated assessment of customer service through voice recognition
NSERC Engage (with Seth's Hospitality Services Inc.)
2014-2015, National, $25,000

Optimizing hearing aids for speech intelligibility, sound quality and emotional speech
Mitacs cluster
2014-2015, National, Co-I; Frank Russo:PI, $138,500

A recognition-by-synthesis architecture for dysarthric speech using deep-belief networks
Nuance Foundation research grant
2013-2014, International, $45,330 USD

Affect recognition (COG1)
GRAND Collaborative Network Investigator
2013-2014, National, $17,000

A control-theoretic model of speech production and recognition for use within prosthetic communication devices
NSERC Discovery grant
2013-2019, National, $120,000

Development of a talker-specific hearing aid
NSERC Engage (with Phonak Ltd.)
2013-2014, National, $25,000

Early Stage grant
University of Toronto
2012, Institutional, $30,000

SpokenWeb: Developing a Comprehensive Web-Based Digital Spoken Word Archive for Literary Research
SSHRC Insight Grant
2012-2014, National, collaborator; Jason Camlot:PI, $301,124

Thotra - Speech enabling technology
Ontario Centres of Excellence Market Readiness award
2012, Provincial, $40,000

Thotra incorporated
RIC VentureStart award
2012, National, $30,000

Towards Articulatory-Based Adaptation in Dysarthric Speech Recognition
NSERC Collaborative Research and Development Grant
2008-2009, National, applicant; Graeme Hirst:PI, $152,895

Towards articulatory-based adaptation in recognition of dysarthric speech
Bell University Labs Research Grant
2007, Institutional, applicant; Graeme Hirst:PI, $75,000

Talks

  • Invited speaker, Artificial intelligence and machine learning, Royal Canadian Navy, Naval Technical Seminar, Halifax NS, 6 June 2024
  • Invited speaker and panelist, L’IA soins: opportunités et risques, Nuit des Idées, Halifax NS, 24 April 2024
  • Invited speaker, Artificial intelligence and machine learning, Royal Canadian Navy, Naval Warfare Officer Symposium, Halifax NS, 1 March 2024
  • Invited speaker, Quis custodiet ipsos custodes?, Responsible Language Models Workshop (ReLM) at AAAI, Vancouver BC, 26 February 2024
  • Panelist, Future Directions and Biggest Obstacles, Machine Learning for Cognitive and Mental Health (CMH) Workshop, Vancouver BC, 26 February 2024
  • Invited speaker, Quis custodiet ipsos custodes?, First Vector NLP Workshop, Toronto ON, 16 February 2024
  • Invited speaker, Working dynamics between humans and automated methods, An Introduction to AI in Health Care, CADTH, 15 February 2024
  • Moderator, Cognitively assistive robots for dementia care, AI for Good, UN ITU, 28 November 2023
  • Invited speaker, The chatbot will see you now, Institute for Comparative Genomics Biodiversity Symposium, Halifax Nova Scotia, 14 November 2023
  • Invited speaker, Artificial intelligence in Long-Term-Care, Care by Design, Halifax Nova Scotia, 13 October 2023
  • Invited speaker, When the axe came into the forest, Absolutely Interdisciplinary, Toronto Ontario, 22 June 2023
  • Keynote, Generative AI, Vector Generative AI workshop, Toronto Ontario, 21 June 2023
  • Panelist, ChatGPT, machine learning and generative AI in healthcare, MaRS Impact Health, Toronto Ontario, 4 May 2023
  • Moderator, Digital Phenotyping and Markers, The Landscape of Early (Neuro)Psychological Changes in AD/ADRD webinar series, NIH, 17 January 2023
  • Panelist, AI in Healthcare panel, bioTEC 2022, Toronto Ontario, 19 November 2022
  • Panelist, Panel on AI Deployment, Mind the Gap: Enabling AI Deployment in Health, Toronto Ontario, 18 November 2022
  • Invited speaker, The Allegory of the OR: Interpreting automated analysis, World Society for Stereotactic & Functional Neurosurgery 2022, Seoul Korea, 4 September 2022
  • Invited speaker, Say 'ah': Speech and language in medicine, UofT AI Conference, Toronto Ontario, 19 February 2022
  • Panelist, Unconventional pathways in Science and Medicine, University of Ottawa Healthcare Symposium, Ottawa Ontario (ostensibly), 29 January 2022
  • Keynote, Say 'ah': Speech and language in medicine, NeuroSphere Healthy Brains Healthy Lives, Montréal Québec (ostensibly), 26 January 2022
  • Keynote, The Allegory of the OR: Interpreting automated analysis, Surgical Safety Network 7th annual meeting, Palm Beach Florida (ostensibly), 8 January 2022
  • Panelist, , 11th Annual Ori Rotstein Lecture in Translational Research, online, 2 November 2021
  • Invited speaker, Say 'ah': Speech and language in medicine, Rotman Research Institute Rounds at Baycrest, Toronto Ontario, 1 November 2021
  • Debater, Why did you do that? Will AI systems ultimately explain their decisions to us?, Robotics and AI symposium, hosted by Ingenuity Labs and Queen's University, Kingston Ontario, 12 October 2021
  • Invited speaker, The Allegory of the OR: Ethics and anaesthetics, Machine Learning in Healthcare, hosted by Toronto Machine Learning Society, Toronto Ontario, 21 July 2021
  • Panelist, Exploring the Roles of AI in Health Sciences Education, National panel hosted by McGill University, Montréal Québec (ostensibly), 22 June 2021
  • Panelist, , Fifth Workshop on Teaching NLP, NAACL-21, Mexico City, Mexico, 11 June 2021
  • Plenary, The allegory of the OR: ethics, anaesthetics, and cybernetics, Canadian Healthcare Optimization Workshop (CHOW) at Canadian Operational Research Society (CORS), Waterloo ON, 7 June 2021
  • Keynote, Ask your doctor if NLP is right for you, 2nd Workshop on NLP for Medical Conversations (NLPMC) at NAACL2021, Mexico City, Mexico, 6 June 2021
  • Panelist, Beyond Patents: Canada's Intellectual Property Puzzle, Innovation Economy Council, online, 3 June 2021
  • Invited speaker and panelist, Natural Language Processing, Deloitte AI Institute Canada, Toronto ON, 6 May 2021
  • Invited speaker, Natural Language Processing, Microsoft/UTMIST Discover AI Upskilling Journey, Toronto ON, 3 May 2021
  • Invited speaker, Machine Learning in the Operating Room, Future Gazing at Northwell Health, New York, USA, 18 March 2021
  • Invited speaker, The allegory of the OR: ethics, anaesthetics, and cybernetics, Schwartz Reisman Seminar Series, Toronto Ontario, 3 March 2021
  • Invited talk, AI and the ethical challenges, Innovation Centre Denmark, Copenhagen, Denmark and Silicon Valley, USA, 11 February 2021
  • Panelist, , Canadian Undergraduate Conference on Healthcare (CUCOH), Kingston Ontario, 23 January 2021
  • Panelist, Decision Making in an Age of Uncertainty, Canadian Agency for Drugs and Technologies in Health (CADTH) Symposium, Virtual, 10 November 2020
  • Invited speaker, Machine Learning in the Operating Room, Canadian Conference for the Advancement of Surgical Education (C-CASE), Montréal Québec, 29 October 2020
  • Invited speaker and panelist, Artificial Intelligence: Changing How We Practice Surgery: Natural Language Processing, Society of American Gastrointestinal and Endoscopic Surgeons (SAGES 2020), Cleveland Ohio, 11 August 2020
  • Invited speaker, Towards explainable AI in the OR, Medical Professional Liability Association CEO/COO meeting, Scottsdale Arizona, 12 March 2020
  • Keynote, Machine Learning In and Out of the OR, Harold and JoAnn Hoffman Lecture - 43rd Annual Meeting of the American Society of Pediatric Neurosurgeons, Nassau Bahamas, 27 January 2020
  • Invited speaker, AI in healthcare and surgery, University Rounds - Ben Alman Research & Science Lecture, Toronto Ontario, 10 January 2020
  • Keynote, Neural models of language, Manulife AI & Advanced Analytics Conference, Toronto, Ontario, 3 December 2019
  • Invited speaker and panelist, OR BlackBox AI: Safe Surgery with Safe AI, Ontario Medical Association, Physicians in the 21st Century, Toronto, Ontario, 22 November 2019
  • Invited speaker, Language and machine learning as a lens into cognition, Machine Learning in Medicine Symposium, Toronto, Ontario, 21 November 2019
  • Invited speaker, What we did last summer: Research at SPOClab, Huawei Annual NLP & Speech symposium, Montréal, Québec, 15 November 2019
  • Invited speaker and panelist, Opening the black box with explainable AI, Techna 2019: Machine/Human Interfaces, Toronto, Ontario, 25 October 2019
  • Invited speaker, Opening the black box with explainable AI, Samsung Medical Centre lecture, Seoul Korea, 4 October 2019
  • Invited speaker, Neural models of language, University of Toronto Scarborough Psychology Seminar Series, Scarborough Ontario, 26 September 2019
  • Invited speaker, Don't drink the Kool-Aid (just sip it), Taking Responsibility for Responsible AI, Munk School of Global Affairs and Public Policy meeting, Toronto Ontario, 26 August 2019
  • Invited speaker, Interpretability, Humans in Loops, Policies and Politics, Forschungszentrum Jülich GmbH Institute for Neuroscience and Medicine, Jülich Germany, 25 July 2019
  • Invited speaker, Explainable AI in healthcare, Element AI speaker series, Toronto Ontario, 3 July 2019
  • Keynote, AI in Healthcare and Surgery, 74th annual meeting of the Canadian Urological Association, Québec City, Québec, 29 June 2019
  • Panelist, AI from Innovation to Healthcare Markets: Barriers and Facilitators, Machine MD, Ottawa Ontario, 1 June 2019
  • Invited speaker, Interpretability, humans in loops, policies and politics, Artificial Intelligence in Medicine Student Society, Toronto Ontario, 27 March 2019
  • Invited speaker and panelist, Regulation and standards for AI in healthcare, CIHR-Health Canada Best Brains Exchange - Artificial Intelligence and Machine Learning in Medical Devices, Ottawa Ontario, 22 February 2019
  • Invited speaker, Natural language processing in clinical systems, Smith School of Business seminar at Queen's University, Toronto Ontario, 19 February 2019
  • Invited speaker, Machine learning in healthcare, Cancer Care Ontario Analytic Rounds, Toronto Ontario, 5 February 2019
  • Keynote, AI in the OR, Surgical Safety Network 4th annual meeting, Palm Beach Florida, 5 January 2019
  • Invited speaker and panelist, The Future of AI in healthcare, Future of Work forum at Munk School of Global Affairs and Public Policy, Toronto Ontario, 6 November 2018
  • Moderator and panelist, The Robot Will See You Now: Artificial Intelligence in Medicine, Toronto Public Library Cutting Edge event, Toronto Ontario, 24 October 2018
  • Debater, Will AI revolutionize suicide prevention?, Canadian Academy of Psychiatric Epidemiology, Toronto Ontario, 26 September 2018
  • Invited speaker, The future of automated healthcare, Inaugural University of Toronto and Tsinghua University Innovations & Entrepreneurship Forum AI Squared, Toronto Ontario, 4 May 2018
  • Invited presenter, , Parliamentary Health Research Caucus on Artificial Intelligence and Machine Learning, and AGE-WELL Day on the Hill, Ottawa Ontario, 1 May 2018
  • Keynote, Natural language processing in clinical systems, University of British Columbia, Text Analytics Workshop, Vancouver BC, 28 April 2018
  • Invited speaker, Hurdles for machine learning in (clinical) dialogue systems, Thomson Reuters speaker series, Toronto Ontario, 21 February 2018
  • Invited speaker and panelist, Language as a lens into cognition in assessment software, McGill University (Journal of Law and Health) - Changing the Face of Healthcare through Artificial Intelligence: Emerging Ethical and Legal Debates, Montréal Québec, 3 February 2018
  • Invited speaker, The future of automated healthcare, University of Toronto Centre for Ethics speaker series, Toronto Ontario, 30 January 2018
  • Invited speaker, How much care could a robot give if a robot could give care?, University of Gothenburg speaker series, Gothenburg Sweden, 4 December 2017
  • Invited speaker, Machine learning in clinical medicine, Ryerson University, Emerging Topics in Biomedical Engineering (Machine learning for health analytics), Toronto Ontario, 28 November 2017
  • Moderator and panelist, The Robot Will See You Now: Artificial Intelligence in Medicine, Toronto Public Library Cutting Edge event, Toronto Ontario, 21 November 2017
  • Invited speaker, Using technology and speech to track Alzheimer's, AGE-WELL webinar, Toronto Ontario, 14 November 2017
  • Invited speaker, Language as a lens into cognition in assessment software, 13h annual Canadian Undergraduate Conference on Healthcare (CUCOH) at Queen's University, Kingston Ontario, 11 November 2017
  • Invited speaker, Language as a lens into cognition in assessment software, Rotman Research Rounds at Baycrest, Toronto Ontario, 30 October 2017
  • Invited speaker, How much care could a robot give if a robot could give care?, AGE-WELL AGM, Winnipeg Manitoba, 19 October 2017
  • Moderator, Artificial Intelligence in Medicine, Singularity U Summit, Toronto Ontario, 11 October 2017
  • Invited speaker, AI and Health: Opportunities in Research, Roundtable on AI and Health (w/ Helmholtz), Toronto Ontario, 25 September 2017
  • Invited speaker, Speech and Language in Healthcare Informatics, Vector Institute seminar series, Toronto Ontario, 12 September 2017
  • Panelist, Advances in Analytics: Voice recognition, predictive analytics, machine learning, IAGG 2017, San Francisco California, 26 July 2017
  • Invited speaker, Language as a lens into cognition in assessment software, 12th annual Andreae Alzheimer Lecture (the Alzheimer Society), Toronto Ontario, 19 June 2017
  • Invited speaker, Speech and language in healthcare informatics, Carnegie Mellon University seminar series, Pittsburgh Pennsylvania, 17 February 2017
  • Invited speaker, Language as a lens into cognition in diagnostic software, Big-Data and Health symposium, Tel Aviv, Israel, 24 January 2017
  • Invited speaker, Machine learning in clinical medicine, International Genetic Epidemiology Society (Big Data Phenotyping: Opportunities, Analytic Challenges, and Solutions), Toronto Ontario, 24 October 2016
  • Invited speaker, Silicon friends for the golden years, Applied Machine Learning seminar, Yelp, San Francisco California, 12 September 2016
  • Moderator and panelist, The robot will see you now - the revolution of artificial intelligence in medicine, AGE-WELL/Computer Science joint panel, Toronto Ontario, 5 April 2016
  • Invited speaker, Using artificial intelligence and language to assess cognition, Frontiers in Alzheimer's, Toronto Ontario, 14 March 2016
  • Invited speaker, Machine learning in pathological speech, Inaugural seminar, Data in Medicine series, Toronto Ontario, 23 November 2015
  • Invited speaker, Deep assessment of pathological speech, Johns Hopkins University seminar series, Baltimore Maryland, 13 November 2015
  • Invited speaker, Speech interaction with personal assistive robots supporting aging-at-home for individuals with Alzheimer's disease, ASSETS2015 conference, Lisbon Portugal, 28 October 2015
  • Invited speaker, Tongues, brains, Cinderella, and robots: Different ways to handle atypical speech, Université de Laval seminar series, Québec City, Québec, 13 August 2015
  • Invited speaker, Tongues, brains, Cinderella, and robots: Different ways to handle atypical speech, Centre for Intelligent Machines, McGill University seminar series, Montréal Québec, 11 August 2015
  • Invited speaker and panelist, Silicon friends for the golden years, Annual NICE Knowledge Exchange 2015, Toronto Ontario, 28 May 2015
  • Invited speaker, The speaking brain and the listening brain: Classifying received and produced speech in electroencephalography, Engineering Excellence program, Nuance, Burlington Massachussetts, 19 May 2015
  • Invited speaker, Tongues, brains, Cinderella, and robots: Different ways to handle atypical speech, Spoken Language Systems Group, Massachusetts Institute of Technology seminar series, Cambridge Massachussetts, 18 November 2014
  • Invited speaker, Tongues, brains, robots, and Cinderella: Different ways to assess atypical speech, Interactive Media Lab, University of Toronto seminar series, Toronto Ontario, 18 July 2014
  • Invited speaker, Completing the noisy circuit: Systems of feedback in models of dysarthria, Fifth Workshop on Speech and Language Processing for Assistive Technologies, Baltimore Maryland, 26 June 2014
  • Moderator, Transcendence, Panel on Transcendence and the upcoming AI singularity, University of Toronto, Toronto Ontario, 6 May 2014
  • Invited speaker, First we shape our tools: An introduction to SPOClab, Rehab rounds, Graduate Department of Rehabilitation Sciences, University of Toronto, Toronto Ontario, 5 December 2013
  • Invited speaker, Completing the noisy circuit, Seminar series, Toyota Technological Institute at the University of Chicago, Chicago Illinois, 12 November 2013
  • Invited speaker and panelist, Recognizing and transforming atypical speech signals, World Social Science Forum, Montréal Québec, 13 October 2013
  • Invited speaker, Completing the noisy circuit: Systems of feedback in models of dysarthria, Workshop on Speech Production in Automatic Speech Recognition, Lyon France, 30 August 2013
  • Invited speaker, Communicating with machines, Seminar series, University of Sheffield, Sheffield UK, 13 August 2013
  • Panelist, , GRAND-NCE Health & Digital Media Workshop, Toronto Ontario, 17 May 2013
  • Invited speaker, First, we shape our tools: How to build a better speech recognizer, Artificial Intelligence seminar series, University of Waterloo, Waterloo Ontario, 20 January 2012
  • Invited speaker, First, we shape our tools: How to build a better speech recognizer, Computer Science seminar series, University of Concordia, Montréal Québec, 2 December 2011
  • Invited speaker, Towards articulatory-based adaptation in recognition of dysarthric speech, Bloorview Research Institute symposium, Toronto Ontario, 16 November 2009

Media

Service

  • Inaugural Chair
    • SCC mirror committee MC/ISO/IEC JTC 1/SC 42, Artificial Intelligence (2017-2019)
  • Senior Area Chair
    • Speech and Multimodality, ACL 2023 (2023)
  • Chair
    • Toronto Machine Learning Summit (2018)
    • Speech and Hearing Disorders & Perception, Interspeech (2016)
    • Speech Production Measurements and Analyses, Interspeech (2015)
    • Machine Learning II, Canadian Conference on Artificial Intelligence (2011)
  • Co-chair
  • Vice chair
    • SCC mirror committee MC/ISO/IEC JTC 1/SC 42, Artificial Intelligence (2019)
  • President
  • Co-organizer
    • Dalhousie AI Symposium (2024)
    • Vector NLP Workshop (2024)
    • ACL/ISCA Workshop on Speech and Language Processing for Assistive Technologies (2013, 2014, 2015, 2016, 2019)
    • TECHNA 2018 Symposium, Enabling AI in Healthcare (2018)
    • Workshop on Designing Speech, Acoustic and Multimodal Interactions at CHI 2017 (2016-2017)
    • Workshop on Designing Speech and Multimodal Interactions for Mobile, Wearable, and Pervasive Applications at CHI 2016 (2015-2016)
    • Special session on Speech Technologies for Ambient Assisted Living at Interspeech (2014)
  • Secretary-Treasurer
  • Member
    • Scientific and Community Advisory Board, Simons Foundation (2023-present)
    • External Reference Group, Health Canada (2021-present)
    • CIHR College of Reviewers (2017-present)
    • Applied Masters (MScAC) program committee, Department of Computer Science, University of Toronto (2015-2022)
    • Data Science program committee, Department of Computer Science, University of Toronto (2015)
  • Expert member
    • Task Force on AI & Emerging Digital Technologies, Royal College of Physicians and Surgeons of Canada (2018-present)
  • Participant member
    • ICTC Healthtech Advisory Committee (2021-present)
    • IEEE Wellbeing Metrics Standard for Ethical Artificial Intelligence and Autonomous Systems P7010 (2017-2019)
  • Ad hoc member
    • Scientific Advisory Committee on Digital Health Technologies, Health Canada (2019-present)
    • External Advisory Committee on AI in Health, Health Canada (2024-present)
  • Editor
    • MITACS Associate Research Review Committee (2011-2012)
  • Associate editor
    • Journal of Alzheimer's Disease (2016)
  • Editorial board
    • Computational Intelligence (2021-present)
    • Transactions of the ACL (2024-present)
    • Computer Speech & Language (2020-present)
    • PLoS ONE (2020-present)
    • PLoS ONE, Digital Health (2022-present)
    • JMIR Rehabilitation and Assistive Technologies (2016-2018)
  • Guest editor
    • Special Issue of Computer Speech and Language (2014, 2019)
    • PLoS ONE Science of Stories (2018)
    • Special Issue of ACM Transactions on Accessible Computing (TACCESS) (2013-2014)
  • Reviewer (journal)
    • Nature Scientific Data (2023, 2024)
    • Nature (2019, 2021, 2022, 2024)
    • Transactions of the ACL (TACL) (2021-2023, 2024)
    • PLoS ONE, Digital Health (2023)
    • Nature Translational Psychiatry (2023)
    • IEEE Journal of Biomedical and Health Informatics (JBHI) (2019, 2021, 2023)
    • IEEE Transactions on Emerging Topics in Computational Intelligence (2022, 2023)
    • Journal of Alzheimer's Disease (2020, 2023)
    • JMIR (2021, 2022, 2022, 2023)
    • JMIR Artificial Intelligence (2023)
    • ACM HEALTH (2020, 2022)
    • International Journal of Computer Assisted Radiology and Surgery (2022)
    • JAMA Network Open (2022)
    • Computer Speech and Language (2012, 2015, 2021)
    • IEEE Open Journal of Engineering in Medicine and Biology (2021)
    • JAMIA (2021)
    • Journal of Neuroscience Methods (2021)
    • JMIR Medical Education (2021)
    • JMIR Medical Informatics (2021)
    • Nature Communications Medicine (2021)
    • Neural Systems & Rehabilitation Engineering (2013, 2021)
    • Annals of Translational Medicine (2020)
    • Journal of the American Medical Informatics Association (JAMIA) (2020)
    • IEEE Journal of Selected Topics in Signal Processing (2019)
    • IEEE Transactions on Audio, Speech, and Language Processing (2013, 2014, 2016, 2019, 2019)
    • BMJ Open (2018)
    • Computer Methods and Programs in Biomedicine (2012, 2015, 2018)
    • Journal of Geriatric Psychiatry and Neurology (2018)
    • PLOS ONE (2013, 2018, 2018, 2018)
    • University of Toronto Medical Journal (UTMJ) (2016, 2018)
    • Artificial Intelligence in Medicine (2015, 2017)
    • Journal of the Acoustical Society of America (2013, 2014, 2016, 2017)
    • PLOS Computational Biology (2017)
    • IBM Journal of Research and Development (2016)
    • Journal of Current Alzheimer Research (2016)
    • Transactions on Neural Systems & Rehabilitation Engineering (2016)
    • Aphasiology (2014, 2015)
    • Information Retrieval (2015)
    • Speech Communication (2011, 2013, 2015)
    • Biomedical Signal Processing and Control (2014)
    • Sensors (2014)
    • IEEE Transactions on Biomedical Engineering (2014)
    • Assistive Technology (2011, 2013)
    • IEEE Transactions on Neural Networks (2011)
  • Reviewer (grant)
    • Stichting Hanarth Fonds (Netherlands) (2024)
    • AGE-WELL/CFN Catalyst grant for Healthy Aging (2018, 2023)
    • Simons Foundation (2022,2023)
    • Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) Innovation Grants (2021,2022,2023)
    • UK Research & Innovation Medical Research Council (2022, 2023)
    • McGill Healthy Brains for Healthy Lives (2019, 2022)
    • NRC-CIHR Aging in Place (2022)
    • NSERC Discovery (2013, 2014, 2015, 2017, 2018, 2020, 2021, 2022)
    • Swiss National Science Foundation (2022)
    • Temerty Clinical AI Integration Grants (2022)
    • CIFAR International Expert Review Panel (2021)
    • UofT Data Sciences Institute Catalyst Grant (2021)
    • Rosetrees Trust Interdisciplinary Prize (2019)
    • Alzheimer's Society of Canada Training Award (2017, 2018)
    • Canadian Institutes of Health Research (CIHR) Collaborative Health Research Projects - NSERC Partnered (CHRP) (2017, 2018)
    • Ontario Research Fund -- Advanced Health Technologies (2018)
    • NSERC Industrial Research Chair (2017)
    • Oregon Alzheimer's Disease Center (2015, 2016)
    • Alzheimer's Society of Canada (2015)
    • Alzheimer's Association (2013)
    • Mitacs Accelerate (2013)
  • Reviewer (chair)
    • Canada Research Chairs (2023)
  • Reviewer (course)
    • Royal College, AI in Healthcare (2023)
  • Program committee / reviewer (conference)
    • ACL Rolling Review (2021-present)
    • COLM (2024)
    • AAAI Artificial Intelligence for Social Impact (AISI) (2024)
    • AAAI (2021, 2022, 2023, 2024)
    • ACM Conference on Health, Inference, and Learning (CHIL) (2020, 2021, 2022, 2023, 2024)
    • Canadian Conference on Artificial Intelligence (CanAI) (2012, 2014, 2015, 2024)
    • ClinicalNLP Workshop (2020, 2023, 2024)
    • NLP+CSS Workshop (2022, 2024)
    • EMNLP (2016, 2018, 2020, 2021, 2022, 2024)
    • ICLR (2022, 2023, 2024)
    • ICML (2022, 2023, 2024)
    • Interspeech (2017, 2018, 2019, 2021, 2022, 2023, 2024)
    • NeurIPS (2020, 2021, 2022, 2023, 2024)
    • RaPID (2016, 2018, 2020, 2024)
    • WiNLP (2017, 2022, 2024)
    • Workshop on Language Technology for Equality, Diversity, and Inclusion (LT-EDI) (2022, 2024)
    • Workshop on Representation Learning for NLP (RepL4NLP) (2021, 2022, 2023, 2024)
    • ICASSP (2019, 2022, 2023)
    • Workshop on Machine Learning for Health (ML4H) at NeurIPS (2019, 2021, 2022, 2023)
    • EMNLP Demo track (2022)
    • AAAI - Workshop on Human-Centric Self-Supervised Learning (2022)
    • Workshop on Computational Linguistics and Clinical Psychology (CLPsych) (2018, 2019, 2022)
    • ACL-IJCNLP (2021)
    • Annual meeting of the Association for Computational Linguistics (ACL) (2014, 2015, 2019, 2020)
    • AACL-IJCNLP (2020)
    • EACL (2020)
    • International Joint Conference on Artificial Intelligence (IJCAI) (2020)
    • NAACL-HLT (2009, 2019)
    • Workshop on Ethics in Natural Language Processing (2016, 2017, 2018)
    • ACM SIG-ACCESS Conference on Computers and Accessibility (ASSETS) (2016)
    • ACM Workshop on Multimodal Deception (WMDD 2015) (2015)
    • European Signal Processing Conference (EUSIPCO) (2014)
    • Workshop on Speech Production in Automatic Speech Recognition (2013)
    • International Conference on Pervasive Computing Technologies for Healthcare (2012)
    • Symposium on Machine Learning in Speech and Language Processing (2012)
    • Workshop on Speech and Language Processing for Assistive Technologies (2012)
  • Review committee (award)
    • UofT Data Sciences Institute Doctoral Student Fellowship (2022)
    • Canadian AI Best Paper Award (2020)
    • AGE-WELL Trainee Awards (2015, 2017)
    • Alzheimer's Society of Canada (2015)
    • Bloorview Research Institute Post-Doctoral Fellowship (2014)
    • Mark Rochon Leadership Award (2013)
  • Mentor
    • AI4PH, Dalla Lana School of Public Health, University of Toronto (2023-present)
    • Department of Computer Science mentorship program (2012-2013)
  • Judge
    • University of Toronto 2021 ProjectX (2022)
    • Rehabilitation Sciences Sector Research Showcase (2013, 2016)
    • Collaborative Program in Neuroscience Research Day (2015)
    • Toronto Rehab Research Day (2011)
  • Student representative
    • Toronto Rehabilitation Institute Research Advisory Committee (2011-2012)
    • Computer Science faculty, Concordia University (2002-2003)

Contact

902 - 494 - 2211

[my first name]@dal.ca

6050 University Ave, Halifax NS, B3H 1W5

×
XXX