Karen H. Jin
A Short Bio
In 1997 I obtained a Bachelor of Engineering in the Department of Telecommunications and Electrical
Engineering at Shanghai University. In 2001 I obtained a Master of Science in Computer Science from the
University of Windsor, and in 2010 I obtained a PhD in Computer Science from the University of
After obtaining my Bachelor of Engineering I worked at Bell Arcatel Research and Development in
Shanghai as a systems administrator and trainer. After obtaining my Masters of Computer Science I
worked as a full-time Lecturer in the School of Computer Science at the University of Windsor from 2001
to 2007. I worked as a graduate research assistant at the University of Windsor from 2007 to 2010 while
completing my PhD. Since obtaining my PhD in 2010 I have worked as an instructor at Dalhousie
For my M. Sc research thesis I designed and implemented a Fast Dense Matching system for stereo
vision as part of a Federally funded project for Sensori-Motor Augmented Reality for Tele-operation.
For my PhD thesis, I designed and implemented a local approximation algorithm for multiply-sectioned
Bayesian networks. My current research interests are in Artificial Intelligence, specifically,
probabilistic uncertainty reasoning. I have 10 publications in these areas.
I plan to extend my research in multi-agent probabilistic reasoning to apply to probabilistic
robotics. The issue of probabilistic reasoning and programming for cooperative robots remains poorly
explored and existing models are too restrictive to characterize robot interaction in complex
environment. I plan to extend the current modeling tools and inference algorithms in multi-agent
domains towards that direction.
I have 10 years experience as a full time lecturer and instructor in computer science at the
University of Windsor and Dalhousie University. I have taught large first year programming language
courses as well as courses in data structures, and more advanced courses in object oriented programming
and programming languages.
Recently, at Dalhousie and elsewhere, diversity in the classroom has been receiving attention.
University educators realize the need to adjust teaching styles to match the learning styles in a
culturally diverse student body. University administrators are interested in retention and satisfaction
rarings from international students attending university. In computer science specifically the numbers
of female students are a cause for concern both in the university setting and in the workplace. I was
recently (in 2011) instrumental in establishing a workshop on diversity in the classroom. This workshop
attracted a lot of interest and has expanded series of five workshops around the theme of
"diversity in the classroom". There is much more research and development that needs to be
done in this area, both in university and in industry, and I am focussed on this issue particularly as
it relates to students graduating from the Chinese school system.
I am teaching the following course in Fall 2011
- CSCI 1100: Computer Science
All materials are available in BLS.
- CSCI 3136: Principle of Programming Languages.
- Karen Jin and Dan Wu. Optimizing Local Computation for Cooperative
Probabilistic Reasoning. In Proc. of the 24th International FLAIRS Conference
- Karen Jin and Dan Wu. Local Importance Sampling in Multiply Sectioned
Bayesian Networks. In Proc. of the 23th International FLAIRS Conference
- Karen Jin and Dan Wu. MA-DBN: Modeling Cooperative Agents for
Approximate Online Monitoring. In Proc. of the 21st IEEE Int'l Conference on Tools with
Artificial Intelligence 2009.
- Dan Wu, Nasreen Tania and Karen Jin. Heuristic Assignment of CPDs for
Probabilistic Inference in Junction Trees. In Proc. of the 21st IEEE Int'l
Conference on Tools with Artificial Intelligence 2009.
- Karen Jin and Dan Wu. On Designing Approximate Inference Algorithms for
Multiply Sectioned Bayesian Networks. In Proc. of the 2009 IEEE
International Conference on Granular Computing 2009.
- Karen Jin and Dan Wu. An Architecture for Iterative Multi-agent Belief
Updating. In Proc. of the 2008 International Conference on Computer Science and Software
- Karen Jin and Dan Wu. Marginal Calibration in Multi-agent Probabilistic
Systems. In Proc. of the 20th IEEE Int'l Conference on Tools with Artificial Intelligence
- Karen Jin and Dan Wu. Towards a Faster Inference Algorithm in Multiply
Sectioned Bayesian Networks. In Proc. of the 21st Canadian Conference on Artificial
- Dan Wu and Karen Jin. Demystify the Messages in the Hugin Architecture
for Probabilistic Inference and Its Application. In Proc. of the 18th International
FLAIRS Conference 2006.
- Boubabuer Boufama and Karen Jin. Towards a fast and reliable dense
matching algorithm. In Proceedings of International Conference of Vision
Interface 2002. This paper has also appeared in Society of Manufacturing Engineers MS03-119
as a technical paper.