Adam Wei

Adam Wei

EECS Ph.D. Candidate

MIT

Biography

I am a second year Ph.D. student at MIT advised by Prof. Russ Tedrake. My current research focuses on two main directions: 1) Understanding and improving how different data sources can be used in robot imitation learning; and 2) algorithmic improvements for generative modeling in robotics. Prior to MIT, I worked on model-based control for contact-rich systems.

I completed my undergraduate degree at the University of Toronto where I worked with Prof. Andreas Moshovos. I also spent a formative summer at the University of Pennsylvania where I was advised by Prof. Michael Posa.

I am grateful to be funded by the NSF Graduate Research Fellowship and the NSERC Postgraduate Scholarship (Doctoral).

Interests
  • Robotics
  • Imitation Learning
  • Simulation
  • Controls
Education
  • EECS Ph.D. Candidate, 2023-Present

    MIT

  • B.Eng in Electrical Engineering, 2023

    University of Toronto

  • IB Diploma, 2019

    Colonel By Secondary School

Publications

(2025). Empirical Analysis of Sim-and-Real Cotraining Of Diffusion Policies For Planar Pushing from Pixels. IROS 2025 Submission.

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(2024). Consensus Complementarity Control for Multicontact MPC. IEEE Transactions on Robotics (IEEE RAS TC Best Paper Award 2024).

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(2022). Framework and Software for Real-Time Multi-Contact Model Predictive Control. RSS Workshop.

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