- Assistant Professor
- Department of Computer Science
- The College of New Jersey
- P.O. Box 7718, 2000 Pennington Rd., Ewing, NJ 08628
- Office location, hour, and contact information (Best way to contact: Please use email)
My research interests span around artificial intelligence, machine learning, computer vision, multimedia, and pattern recognition. In general, my research goal is to fill in the gap between individual human decision making process and the group-level behavior, which typically based on distributed or decentralized individual decisions, and eventually devise a generalized computational model to reproduce them. We hope the model can cover both low level multi-modal input processing and high level human cognitive processes in a unified framework. To this end, I am actively conducting research on following topics:
- Crowd Motion and Behavior Analysis
- Distributed Machine Learning
- Computational Models for Multimedia Analysis
I have participated in other application research projects using general machine learning methods and algorithms, too, including:
You can download some of the research code I (or my student under my supervision) wrote from my github repository.
- February 25, 2020: I will co-organize an IJCAI-PRICAI 2020 workshop on “Neuro-Cognitive Modeling of Humans and Environments.”
- February 7, 2020: I will present a new game-based model assignment for AI classes in EAAI 2020.
Note for TCNJ students: If you are interested in shadowing, mentored research, capstone project, or any other research project with me, please contact me via email.
Short Bio: I joined The College of New Jersey in Fall 2016. Before joining TCNJ, I earned my Ph.D. degree in Computer Science at Rutgers, The State University of New Jersey working with Prof. Vladimir Pavlovic in SEQAM group. I also conducted research in medical informatics for my M.S. and B.Eng. degrees at Sogang University, working with Prof. Saejoon Kim. I was fortunate to work in various industrial and government organizations, detailed in my LinkedIn page.