People · Co-founder & CTO · Simulation & learning
Matt Bennice.
Simulation-driven robot control, imitation and reinforcement learning at fleet scale, and the sim-to-real discipline behind robots that work outside the lab. Google X, Everyday Robots, DeepMind, Wing, Stack AV, 1X, Cruise.
Simulation-driven controlImitation learningReinforcement learning at scaleSim-to-real transferFleet learningHuman-robot interaction
01 / Selected publications
The papers.
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
Jump-Start Reinforcement Learning
Practical Visual Deep Imitation Learning via Task-Level Domain Consistency
VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration
Interactive Multi-Robot Flocking with Gesture Responsiveness and Musical Accompaniment
Full record on dblp ↗
02 / Granted patents
The filings.
Simulation driven robotic control of real robot(s)
Simulation driven robotic control · continuation, granted 2025 under Google DeepMind
Re-simulation of recorded episodes
Imitation learning for training and refining robot control policies
Simulating multiple robots in virtual environments
Injecting noise into robot simulation
Single iteration, multiple permutation robot simulation
Imitation robot control stack models
The complete family of 8 granted US patents in simulation-driven robotics, plus international filings, assigned to X Development, Google, and Google DeepMind. Patents are inventor credentials assigned to prior employers.
At Cereal
At Cereal, Matt owns the world loop: the always-on simulation that mirrors the home, verifies every plan before a body moves, and turns recorded operation back into training and verification data.