Adam Wei

Adam Wei

EECS Ph.D. Candidate

MIT

Biography

I am a third 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 with a focus on learning from out-of-distribution or low-quality data. Prior to MIT, I worked on model-based control for contact-rich systems with Prof. Michael Posa.

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

CV (last updated Sept 2025)

Interests
  • Robotics
  • Imitation Learning
  • Generative Modeling
  • 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

Selected Publications

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

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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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Publications

(2025). How Well do Diffusion Policies Learn Kinematic Constraint Manifolds?. Under Review ICRA 2026.

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

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