Nolan Fey

I'm a Ph.D. student in the Improbable AI Lab at MIT Computer Science and Artificial Intelligence Lab (CSAIL), where I'm advised by Pulkit Agrawal. My research focuses on giving robots the ability to intelligently move through and interact with the world. I'm grateful to be supported by the NSF GRFP.

I'm also a founding researcher at Minerva Humanoids, a San Francisco-based startup deploying humanoid robots in hazardous environments.

Previously, I received a B.S. in Electrical Engineering with a Second Major in Physics at Notre Dame, where I worked with Patrick Wensing and Michael Lemmon. I've also been fortunate to intern at the U.S. Naval Research Lab in D.C. and NASA JPL.

Email  /  Google Scholar  /  X  /  GitHub

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Research

I equip robots with foundational motion skills. Recently I've been especially interested in sim-to-real transfer: how we can ensure that behaviors learned in simulation will work in the real world.

Unitree G1 softly hitting wall of legos SoftMimic: Learning Compliant Whole-body Control from Examples
Gabriel B. Margolis*, Michelle Wang*, Nolan Fey, Pulkit Agrawal
ICRA 2026

Variable-stiffness humanoid motion imitation enabling gentle contact with the environment for safety and generalization.

Paper / Website / X
Unitree B2/Z1 throwing ball Bridging the Sim-to-Real Gap for Athletic Loco-Manipulation
Nolan Fey, Gabriel B. Margolis, Martin Peticco, Pulkit Agrawal
RSS 2025; Robot Learning Workshop, ICLR 2025 (Oral)

Enhancing the sim-to-real transfer for a legged manipulator by calibrating actuator dynamics and refining whole-body control, enabling agile feats like throwing, lifting, and dragging


Paper / Website / X

MIT Mini Cheetah carrying a case of water A Learning-based Framework to Adapt Legged Robots On-the-fly to Unexpected Disturbances
Nolan Fey, He Li, Nicholas Adrian, Patrick Wensing, Michael Lemmon
L4DC, 2024

A learning-based framework that allows a walking robot to stabilize itself under disturbances neglected by its base controller. We applied it to stabilize the MIT Mini Cheetah as it carried a box of water on its back.


Paper / Video

MIT Mini Cheetah hopping 3D Hopping in Discontinuous Terrain Using Impulse Planning with Mixed-Integer Strategies
Nolan Fey, Robert Frei, Patrick Wensing
IEEE RA-L, 2024.

By approximating each of the robot's stance phases to be impulsive, we enable a mixed-integer program to quickly plan consecutive hops for a quadruped between surfaces while avoiding obstacles.


Paper / Video (IEEE) / Video (YouTube) / Code