Sejong Yoon

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:

In the past, I have participated in application-oriented research projects using general machine learning methods and algorithms, including:

You can download some of the research code I (or my student under my supervision) wrote from my github repository.

Recent Publications (Full List)

  1. D. Li, M. Schwartz, S. Sohn, S. Yoon, V. Pavlovic, M. Kapadia, “Microscopic Modeling of Attentin-based Movement Behaviors,” Transportation Research Part C: Emerging Technologies, Vol. 162, 104583, 2024.
  2. C-J. Chang, D. Li, D.A. Patel, P. Goel, S. Moon, S. Sohn, H. Zhou, S. Yoon, V. Pavlovic, M. Kapadia, “Learning from Synthetic Human Group Activities,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 2024.
  3. K. Hu, S. Yoon, V. Pavlovic, M. Kakapdia, “Toward Realistic Human Crowd Simulations with Data-Driven Parameter Space Exploration,” IEEE International Conference on Artificial Intelligence and Virtual Reality (AIxVR), Los Angeles, CA, USA, 2024.
  4. S. Moon, S. Sohn, H. Zhou, S. Yoon, V. Pavlovic, M. Haris, M. Kapadia, “MSI: Maximize Support-Set Information for Few-Shot Segmentation,” International Conference on Computer Vision (ICCV), Paris, France, 2023.
  5. S. Moon, S. Sohn, H. Zhou, S. Yoon, V. Pavlovic, M. Haris, M. Kapadia, “HM: Hybrid Masking for Few-Shot Segmentation,” The 17th European Conference on Computer Vision (ECCV), Tel Aviv, Israel, 2022.
  6. S. Sohn, M. Lee, S. Moon, G. Qiao, M. Usman, S. Yoon, V. Pavlovic, M. Kapadia, “A2X: An end-to-end framework for assessing agent and environment interactions in multimodal human trajectory prediction,” Computers & Graphics, Vol. 106, Pages 130-140, 2022.
  7. S. Sohn, S. Moon, H. Zhou, M. Lee, S. Yoon, V. Pavlovic, M. Kapadia, “Harnessing Fourier Isovists and Geodesic Interaction for Long-Term Crowd Flow Prediction,” The 31st International Joint Conference on Artificial Intelligence (IJCAI), Vienna, Austria, 2022.
  8. M. Lee, S. Sohn, S. Moon, S. Yoon, M. Kapadia, V. Pavlovic, “MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Prediction,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, USA, 2022.

Active Grants

Note for Prospective Students

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.