Organizing a workshop on "Interactive Learning with Implicit Human Feedback" at ICML 2023.

New paper accepted to CDC on "Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning", where we propose a method for repairing feature representations to better generalize across states!

I accepted a visiting Research Scientist position at the Boston Dynamics AI Institute starting August 2023!

I gave an invited talk at the CHAI Workshop.

I gave an invited talk at the Stanford Robotics Seminar. Check out the talk here!

I accepted an offer to join the Department of Aeronautics and Astronautics in the School of Engineering at Massachusetts Institute of Technology (MIT) starting Fall 2024!

I published a patent with the NVIDIA Robotics team on a new concept training technique for machine learning based on our paper on "Learning Perceptual Concepts by Bootstrapping from Human Queries"!

New paper accepted to ICML, "Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-time Policy Adaptation", where we propose a human-in-the-loop framework for robots to recover from distribution shift failures.

Giving an invited talk at the Microsoft Research Seminar Series.

Organizing a workshop on "Aligning Robot Representations with Humans " at the Conference on Robot Learning 2022.

Giving an invited talk at the Robotics Colloquium at UW.

Giving an invited talk at the New Trends in Aerospace Seminar Series at MIT.

New paper accepted to HRI, "SIRL: Similarity-based Implicit Representation Learning", where we enable robots to learn salient feature representations by asking humans to gauge how similar different behaviors are.

I gave an invited talk at the Robotics Seminar at Cornell.

I was invited to speak at University of Utah's CS 6960: Human-AI Alignment graduate course.

I gave an invited talk in the Robot Autonomy and Interactive Learning (RAIL) Lab at Georgia Tech.

Our paper on Time-Efficient Reward Learning via Visually Assisted Cluster Ranking has been accepted to the Human-in-the-loop Learning (HILL) Workshop at NeurIPS 2022.

I gave an invited talk at the Illinois Robotics Seminar at UIUC.

I gave an invited talk in the Intelligent and Interactive Autonomous Systems Group (ILIAD) Group at Stanford.

I am grateful to have been selected for the Rising Star in EECS Academic Career Workshop!

I gave an invited talk at the Workshop on Complex Feedback in Online Learning at ICML.

Co-organized a workshop on "Social Intelligence in Humans and Robots" at Robotics: Science and Systems 2022.

New paper accepted to IROS, "Teaching Robots to Span the Space of Functional Expressive Motion", where we enable people to efficiently teach robots expressive motions during task execution.

New paper accepted to Robotics and Automation Letters, "Learning Perceptual Concepts by Bootstrapping from Human Queries". In this work, we ask for human input to learn a low-dimensional variant of the perceptual concept, then use it to generate a larger data set for learning the concept in the high-dimensional space.

I gave an invited talk at Apple's AI/ML seminar.

I was named a Robotics: Science and Systems Pioneer!

Our paper on  Aligning Robot Representations with Humans has been accepted to the  Workshop on Collaborative Robots and the Work of the Future, at ICRA 2022.

Our paper "Inducing Structure in Reward Learning via Feature Learning" was accepted at the International Journal of Robotics Research.

I gave an invited talk at Aware-learning: how to benefit from priors, a workshop at the Conference on Decision and Control.

I gave an invited talk at MIT's Interactive Robotics Group.

I was named an Apple Scholar in AI and Machine Learning (AI/ML)!

Our journal paper "Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections" received an Honorable Mention for the 2020 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award.

Our paper on reward learning using feature traces, a novel type of human input, was nominated for a Best Paper Award at the ACM/IEEE International Conference on Human-Robot Interaction 2021.

Our paper "Dynamically Switching Human Prediction Models for Efficient Planning" was accepted at the IEEE International Conference on Robotics and Automation 2021.

Our paper "Situational Confidence Assistance for Lifelong Shared Autonomy" was accepted at the IEEE International Conference on Robotics and Automation 2021.

Our paper "LESS is More: Rethinking Probabilistic Models of Human Behavior" won Best Paper Award at the ACM/IEEE International Conference on Human-Robot Interaction 2020.