Keyvan Majd
Keyvan Majd
Keyvan Majd
Research Engineer @ Toyota Research Institute in NA

I am a Research Engineer at Toyota Research Institute of North America (TRINA). My research interests include motion planning and control, safe robot learning, human-robot interaction, and generative models for robotics.

I received my Ph.D. in Computer Science from Arizona State University, advised by Heni Ben Amor and Georgios Fainekos.

Past research projects
Safety-aware Expansion for Neural Network Repair

Safety-aware Expansion for Neural Network Repair
iROS'23

Inspired by the popular cascade-correlation algorithm, this project introduces a safety-aware growing neural network method aimed at expanding neural networks with new hidden units dedicated exclusively to responding to faulty samples.
Safety-aware Neural Network Repair for Robotic Systems with Predictive Models

Safety-aware Neural Network Repair for Robotic Systems with Predictive Models
IROS'2024

This project presents a two-step supervised learning approach for safety-aware robot learning, using predictive models to enforce explicit and implicit contraints on the policy.
Safe Robot Learning in Assistive Devices through Neural Network Repair

Safe Robot Learning in Assistive Devices through Neural Network Repair
CoRL'22 - NeurIPS'22

This project presents NNRepLayer: the first repair technique applied to a real physical system.
Joint Communication and Motion Planning for Cobots

Joint Communication and Motion Planning for Cobots
ICRA'21

This project unifies communication and motion planning to enrich human-robot interaction, to prevent potential deadlocks and freezing situations, and to maintain the planning efficiency in terms of raveled distances.
Risk-bounded Motion Planning and Control in Confined Dynamic Environment

Risk-bounded Motion Planning and Control in Confined Dynamic Environment
iROS'21 - L-CSS'20

This project addresses the "Freezing Robot" problem in dynamic confined environments. We introduced a method to bound the probability of collision to a given value in finite-time.
News
Jan 2026
Our paper "Safe Model Predictive Diffusion with Shielding" has been accepted to ICRA 2026!
Jun 2025
Two papers accepted: "GPU-Accelerated Barrier Rate MPPI Control for Tractor-Trailer Navigation" at ITSC 2025, and "Robot Behavior Adaptation in Physical Human-Robot Interactions" at IROS 2025!
Dec 2024
I successfully defended my Ph.D. dissertation "Safe Robot Learning with Neural Network Repair" at Arizona State University!
Oct 2024
Joined Toyota Research Institute of North America as a Research Engineer, working on autonomous maneuvering and motion planning.
Jun 2024
Our paper "Repairing Neural Networks for Safety in Robotic Systems using Predictive Models" has been accepted to IROS 2024!
Dec 2022
Our paper "Certifiably-correct Control Policies for Safe Learning and Adaptation in Assistive Robotics" received a Best Paper Award (2nd Runner-up) at NeurIPS 2022 Robot Learning Workshop!
Sep 2022
Our paper "Safe Robot Learning in Assistive Devices through Neural Network Repair" has been accepted to CoRL 2022!