Second-year PhD Student in Electrical Engineering · University of Notre Dame
I study how intelligent robots can understand and adapt to people. At Notre Dame's Intelligent Interaction Research Lab, advised by Prof. Zhi Zheng, my research focuses on autonomy-supportive robot assistance, multimodal behavior understanding, and decision-making under uncertainty.
Designing an Autonomy-POMDP that infers a user's latent autonomy from gaze observations and adapts robot assistance accordingly. I developed an LLM simulation with nine user personas and am extending this approach to real-world collaborative tasks.
Studying how autistic workers perceive industrial robots as potential collaborators. Applied Self-Determination Theory to interviews and contributed to preliminary design principles for neuroaffirming human–robot interaction.
Analyzing preschoolers' anticipatory gaze and attention, including eye-tracking feature extraction, data quality assessment, and behavioral analysis pipelines.
Worked on automatic robotic suturing assessment with Video Swin Transformers and technical-skill prediction, alongside single-view 4D reconstruction using point clouds and learned geometric representations.
Education
University of Notre Dame · South Bend, IN
Columbia University · Advanced Master Research Track
Tesla Scholarship & MS EE Honor Program
Research & teaching
Intelligent Interaction Research Lab · Prof. Zhi Zheng
Introduction to Electrical and Computer Engineering
ZKLab · Prof. Zoran Kostic
Reinforcement Learning; Neural Networks & Deep Learning
E. Kim, Y. Hu, K. Kim, V. V. Izaac, K. Stastny, C. Branscome, J. Carpini, C. H. Park, Z. Zheng, M. Jeon, A. Scarpa, and S. Kim, “Supporting autistic workers through industrial robots: An exploratory self-determination theory analysis of requirements and design principles,” in Proc. 35th IEEE Int. Conf. Robot and Human Interactive Communication (RO-MAN), Kitakyushu, Japan, Aug. 2026.
E. Fox, Y. Hu, M. McEllin, Y. Kuo, Z. Zheng, and C. Clements, “Evaluating ePeekaboo: A novel eye tracking paradigm for studying anticipatory behavior in preschool-aged children,” poster presented at the Purdue Autism Research Conference, 2026.
S. Choksi, S. Narasimhan, M. Ballo, M. Turkcan, Y. Hu, C. Zang, A. Farrell, B. King, J. Nussbaum, A. Reisner, Z. Kostic, G. Taffurelli, and F. Filicori, “Automatic assessment of robotic suturing utilizing computer vision in a dry-lab simulation,” Artificial Intelligence Surgery, vol. 5, no. 2, pp. 160–169, 2025. doi: 10.20517/ais.2024.84.