Student Researcher

Skyler (Sijie) Han

Embodied AI • Computer Vision • Robotics

I am a third-year undergraduate student at the University of Toronto, pursuing a Bachelor of Applied Science in Engineering Science with a major in Robotics and a minor in Artificial Intelligence. I am also fortunate to be a research intern at CSAIL, MIT working with Prof. Antonio Torralba. My research interests lie at the intersection of embodied AI, computer vision, and robotics, with a particular focus on dataset generation for robust embodied agents.

BASc Engineering Science (Robotics, AI) — University of Toronto Toronto, ON
Sijie (Skyler) Han portrait

Publications

Selected papers. Full list on Google Scholar.

2026

K. Swain, S. Han, A. Torralba. VirtualEnv: A Platform for Embodied AI Research. AAAI 2026.

2025

K. Darvish, A. Sohal, A. Mandal, H. Fakhruldeen, N. Radulov, Z. Zhou, J. Choi, S. Han, B. Zhang, J. Chae, S. Veeramani, A. Wright, Y. Wang, H. Darvish, Y. Zhao, G. Tom, H. Hao, M. Bogdanovic, G. Pizzuto, A. Cooper, A. Aspuru Guzik, F. Shkurti, A. Garg. MATTERIX: Towards a Digital Twin for Robotics-Assisted Chemistry Lab Automation. Nature Computational Science, 2025.

2025

S. Okuboyejo, S. Han, S. Jha, C. Eneja, R. Orji. Insights from User Reviews to Improve Suicide Prevention Apps: A Machine Learning and Thematic Analysis-Based Approach. International Journal of Human–Computer Interaction, 2025.

Experience

Selected roles.

Embodied AI Research Intern — CSAIL, MIT

Sep 2024 – Present · Cambridge, MA (Remote)

  • Co-developed VirtualEnv, a UE5 simulation platform with procedural scene generation and benchmarking.

AI/ML Intern — Autodesk

Jan 2026 – Apr 2026 · Toronto, ON

  • Built robust ML tooling and trained animation models for Autodesk Maya.

Robotics Research Intern — People, AI, & Robots Research Group (University of Toronto)

Apr 2024 – Aug 2024 · Toronto, ON

  • Built chemistry-focused digital twins in Isaac Sim for safe training and validation.

Team Member — Tracking Division — aUToronto (Autodrive)

Sep 2023 – Jun 2024 · Toronto, ON

  • Benchmarked tracker performance with multimodal ground truth; improved object persistence by 23%.