Bohan Yang

This Fall (2026), I'll be starting as a CS PhD student at UW–Madison.

Hi! I'm an undergrad studying Computer Science at Cornell University, advised by Tapomayukh Bhattacharjee on assistive robotics and human-in-the-loop robot learning at the Cornell EmPRISE Lab.

I'm interested in building physical AI systems that learn from experience after deployment, adapting through interaction to handle long-tail failures in the real world.

Email  /  CV  /  Scholar  /  GitHub  /  LinkedIn

profile photo

News

May 2026 Honored to receive the NSF INTEGRATE Research Training Program Fellowship.
Mar 2026 Attending HRI '26 in Edinburgh, Scotland. Check out our paper: A Human-in-the-Loop Confidence-Aware Failure Recovery Framework for Modular Robot Policies.
Jun 2025 Spending the summer at the Cornell BURE program doing research on VLA models.

Selected Publications

E-MPC project thumbnail Beyond Failure Recovery: An Engagement-Aware Human-in-the-loop Framework for Robotic Systems
Jiaying Fang, Joyce Yang, Zhanxin Wu, Bohan Yang, Tapomayukh Bhattacharjee
RSS, 2026
project page

We propose Engagement-aware MPC (E-MPC), a user-engagement-aware method that plans interaction to maintain engagement while respecting a workload constraint.

Modular HIL project thumbnail A Human-in-the-Loop Confidence-Aware Failure Recovery Framework for Modular Robot Policies
Rohan Banerjee, Krishna Palempalli*, Bohan Yang*, Jiaying Fang, Alif Abdullah, Tom Silver, Sarah Dean†, Tapomayukh Bhattacharjee
HRI, 2026
project page / arXiv / code

A framework for modular policies that combines module-level uncertainty with models of human intervention cost to decide when and which module to query, evaluated on synthetic experiments and a robot-assisted bite acquisition system.

Teaching

Teaching Assistant, Cornell University.

Spring 2026 CS 4740 / CS 5740: Natural Language Processing — Prof. Tanya Goyal
Fall 2025 CS 4787 / CS 5777: Principles of Large-Scale Machine Learning — Prof. Chris De Sa
Spring 2025 CS 4789 / CS 5789: Introduction to Reinforcement Learning — Prof. Wen Sun

Template adapted from Jon Barron.