Dr. Christian G. Liu, Ph.D. Halifax, Canada
+1-902-719-7884 • chris.liu@dal.ca • linkedin.com/in/drchrisliu
Ph.D. in Computer Science | Postdoctoral
Researcher | Senior Software Engineer
Dr. Christian Liu, based in Halifax, Canada, is a postdoctoral researcher and senior software engineer specializing in blockchain technology research. He received his Ph.D. in Computer Science from Dalhousie University and holds Master’s degrees in Computer Science from both Concordia University and Dalhousie University. With over twenty years of experience in the IT industry, Dr. Liu has led significant projects and teams at global tech companies like Ericsson, CGI, IBM, and Samsung. Currently, he continues his research at Dalhousie University as a full-time postdoctoral fellow and imparts his extensive knowledge as an educator.
Ericsson, Montreal, QC (7/2007 – 11/2011)
CGI Inc., Halifax, NS (1/2012 – 2/2015)
IBM Canada Ltd.,
Halifax, NS (4/2015 – 5/2018)
Samsung (Nanjing) Research Centre (5/2018 – 8/2018)
Dalhousie University (9/2018 – Present)
Dalhousie University, Halifax, NS
· Postdoctoral Researcher / Teaching Fellow (4/2024 – Present)
· Doctoral Researcher / Teaching Fellow (5/2018 – 4/2024)
Instructor Roles:
Dalhousie University, Halifax, NS
1. CSCI 2133 - Rapid Prototyping (2019)
2. CSCI 4140 - Advanced Database (2017, 2018, 2021 Summer & Fall Terms)
3. MCDA 5560 - Business Intelligence (2018 Summer & Fall)
4. CSCI 5408 - Data Warehousing (2018 Winter)
Teaching Assistant Roles:
Dalhousie University, Halifax, NS
1. CSCI 6313 - Blockchain (2022 Summer Term, 2023 Summer & Fall Terms)
2. CSCI 4140 - Advanced Database (2019 Fall, 2020 Winter, Summer & Fall, 2022 Winter, Summer & Fall, 2023 Summer & Fall)
3. CSCI 5409 - Cloud Computing (2020 Summer)
Dalhousie University, Halifax, NS (2021-2024)
Dalhousie University, Halifax, NS (2019-2020)
Concordia University, Montreal, QC (2005-2007)
For a detailed list of publications, please refer to the end of my resume.
My academic journey at Dalhousie University involved extensive exploration of blockchain technology and its applications, from theory to practical deployment. This foundation was built upon a solid grounding in computer science obtained at Concordia University. My research aims to understand how blockchain technology can revolutionize various industries and address real-world challenges through innovative solutions. Professional certifications and participation in development programs have enhanced my technical skills and teaching capabilities, reflecting my dedication to continuous learning and advancement in the fields of computer science and blockchain research.
1. Liu, C. 2021. FSM for Modeling for Off-Blockchain Computation. Faculty of Graduate Studies Online Theses. Dalhousie University, Halifax, Nova Scotia, Canada. http://hdl.handle.net/10222/80335. Master Thesis.
2. Bodorik, P., Liu, C., Jutla, D. (2021). Using FSMs to Find Patterns for Off-Chain Computing: Finding Patterns for Off-Chain Computing with FSMs. In 2021 The 3rd International Conference on Blockchain Technology (ICBCT '21), March 26-28, 2021, Shanghai, China. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3460537.3460565.
3. Liu, C., Bodorik, P., Jutla, D. (2021a). A Tool for Moving Blockchain Computations Off-Chain. In Proceedings of 2021 3rd ACM International Symposium on Blockchain and Secure Critical Infrastructure (BSCI'21), June 3-7, 2021, Virtual Event, Hong Kong. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3457337.3457848. Acceptance rate: 36.7%.
4. Liu, C., Bodorik, P., & Jutla, D. (2021b). From BPMN to smart contracts on blockchains: Transforming BPMN to DE-HSM multi-modal model. 2021 International Conference on Engineering and Emerging Technologies (ICEET), 1–7. https://doi.org/10.1109/ICEET53442.2021.9659771. Acceptance rate: 30%.
5. Liu, C., Bodorik, P., Jutla, D. (2022a). Automating Smart Contract Generation on Blockchains Using Multi-modal Modeling. Journal of Advances in Information Technology (JAIT). https://doi.org/10.12720/jait.13.3.213-223. Acceptance Rate: 5%, CiteScore: 4.2.
6. Liu, C., Bodorik, P., Jutla, D. (2022b). Supporting Long-term Transactions in Smart Contracts. 2022 IEEE Fourth International Conference on Blockchain Computing and Applications (BCCA), 11–19. https://doi.org/10.1109/BCCA55292.2022.9922193. Acceptance Rate: 18.89%.
7. Bodorik, P., Liu, C., Jutla, D. (2023). TABS: Transforming automatically BPMN models into blockchain smart contracts. Blockchain: Research and Applications (Elsevier), 100115. https://doi.org/10.1016/j.bcra.2022.100115. Impact Factor: 5.6, CiteScore: 11.3.
8. Liu, C. G., Bodorik, P., & Jutla, D. (2023). Long-Term Blockchain Transactions Spanning Multiplicity of Smart Contract Methods. In Springer BlockSys: Blockchain and Trustworthy Systems. https://doi.org/10.1007/978-981-99-8104-5. Acceptance rate: 27.8%.
9. Liu, C., Bodorik, P., & Jutla, D. (2024). Transforming Automatically BPMN Models to Smart Contracts with Nested Trade Transactions (TABS+). Distributed Ledger Technologies: Research and Practice. https://doi.org/10.1145/3654802.
10. Liu, C. G. (2024). Supporting Long-term Transactions in Smart Contracts Generated from Business Process Model and Notation (BPMN) Models. Faculty of Graduate Studies Online Theses. Dalhousie University, Halifax, Nova Scotia, Canada. http://hdl.handle.net/10222/83441. PhD Dissertation.