Assistant Professor
Computing Sciences
College of Engineering, Technology, and Architectureminli@hartford.edu UT 302G
Dr. Mingjun Li joined the University of Hartford as an Assistant Professor in the Department of Computing Sciences in Fall 2025. He earned his Ph.D. in Computer Science from Clarkson University and his M.S. in Computational Sciences from Marquette University.
Dr. Li’s research focuses on machine learning, deep learning, 2D/3D computer vision, human–robot interaction, and virtual reality. His recent work includes developing advanced deep learning models for VR-based biometric authentication and human motion forecasting, as well as building large-scale multi-modal datasets for the human–robot interaction community.
In addition to his research, Dr. Li is an accomplished educator with extensive teaching experience in computer graphics, algorithms, deep learning, and introductory computer science. He has also mentored numerous Ph.D., M.S., and undergraduate students, fostering their growth in technical skills, research methodology, and academic writing.
Beyond the classroom and lab, Dr. Li is active in the scholarly community, serving as a reviewer for leading conferences and journals such as IEEE VR, NeurIPS, and ICME. His passion lies in creating intelligent, human-centered computing systems that are context-aware, personalized, and trustworthy, bridging the gap between cutting-edge AI research and real-world applications.
- Li’s research focuses on machine learning, deep learning, 2D/3D computer vision, human–robot interaction, and virtual reality. His recent work includes developing advanced deep learning models for VR-based biometric authentication and human motion forecasting, as well as building large-scale multi-modal datasets for the human–robot interaction community.
- During his Ph.D, he has mentored numerous Ph.D., M.S., and undergraduate students, fostering their growth in technical skills, research methodology, and academic writing.
- “Cross-System Virtual Reality (VR) Authentication Using Transformer-Based Trajectory Forecasting,” in 22nd EuroXR International Conference (EuroXR 2025);
- “Multimodal Cross-System Virtual Reality (VR) Ball Throwing Dataset for VR Biometrics,” Data in Brief;
- “Predicting 3D Motion from 2D Video for Behavior-Based VR Biometrics,” in 2025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR 2025);
- “Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication,” in 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR 2024);
- “Evaluating Deep Networks for Detecting User Familiarity with VR from Hand Interactions,” in 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR 2024);
- “Studying How Object Handoff Orientations Relate to Subject Preferences on Handover,” in 2023 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO);
- End-to-End Latency Optimization of Multi-view 3D Reconstruction for Disaster Response,” in 2022 10th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud).