TEA Lab | Virginia Tech

PhD Student

Mon, 01 Jan 0001 00:00:00 +0000

About me

I am a PhD student at Virginia Tech, where I am working with Prof. Simon Stepputtis. Prior to that, I received my master’s degree at the University of California, San Diego, where I had the opportunity to work with many outstanding researchers, including Prof. Sylvia Herbert, Prof. Michael Yip, Prof. Sicun Gao and Dr. Nikhil Uday Shinde.

PhD Student

Mon, 01 Jan 0001 00:00:00 +0000

About me

I’m currently interested in developing physics-aware neurosymbolic policies for efficient, interpretable, and generalizable control of robot-environment interaction. My previous research has focused on data-driven modeling of nonlinear dynamics in contact- and vibration-rich physical systems.

PhD Student

Mon, 01 Jan 0001 00:00:00 +0000

About me

My research interests are dexterous manipulation, robot learning, and embodied intelligence, with a particular focus on how robots can learn transferable manipulation skills from human demonstrations. Outside research, I enjoy science fiction and film, especially works that explore consciousness, identity, and how human subjectivity is formed.

PhD Student

Mon, 01 Jan 0001 00:00:00 +0000

About me

I am currently a first year PhD. student, focusing on explainable AI, life-long learning and applications of VLMs on Robot manipulation tasks. In my daily life, I enjoy mountainbiking, cascading and movies!

PhD Student

Mon, 01 Jan 0001 00:00:00 +0000

About me

I’m a third year Ph.D student, working on neural system identification for dynamical systems, particularly interpretable models. Outside of research, I enjoy knitting, spending time with my cat and baking!

Two papers accepted at NeurIPS 2026

Fri, 25 Sep 2026 00:00:00 +0000

Two papers were accepted at NeurIPS 2026: “Learning When to Think: Adaptive Internal Computation for Reinforcement Learning” in the main conference, and our position paper “Neurosymbolic AI is a Strong Technical Foundation for Trustworthy, Deployable AI by Design”, with collaborators at Carnegie Mellon University, in the position paper track.

TEA Lab at IROS 2026

Tue, 15 Sep 2026 00:00:00 +0000

We are presenting three papers at IROS 2026: "From Local Corrections to Generalized Skills: Improving Neuro-Symbolic Policies with MEMO" in the main conference, “TRACT: Bimanual Cable Insertion via Tactile Tension Regulation” at the Touch-to-Action workshop, and “Learning Object-Centric Barrier Functions for Contact-Rich Interaction in Clutter” at the Learning and Formal Methods for Robotics workshop.

Three new PhD students join the lab

Mon, 17 Aug 2026 00:00:00 +0000

Hyeonbeen Lee, Sirui Zhan, and Haixin Jin join TEA Lab as PhD students this fall. Welcome!

POGP presented at RLC 2026

Sun, 16 Aug 2026 00:00:00 +0000

Our work "Learning When to Stop: Prefix-Optimal Dynamic Diffusion Policies for Continuous Control" was presented at the “Reinforcement Learning Conference (RLC 2026)” in Montréal, where it learns a prefix value function at every denoising step to give diffusion policies a parameter-free stopping criterion at test time.

Workshop paper at the Continual RL workshop @ RLC 2026

Sat, 15 Aug 2026 00:00:00 +0000

Our work "Influence-Guided Agent Adaptation for Dynamic Human–AI Collaboration" was presented at the “Continual Reinforcement Learning Workshop @ RLC 2026” in Montréal.

MEMO accepted at IROS 2026

Mon, 15 Jun 2026 00:00:00 +0000

Our work "From Local Corrections to Generalized Skills: Improving Neuro-Symbolic Policies with MEMO", in collaboration with Collab at Virginia Tech, was accepted at “IROS 2026”. MEMO builds a retrieval-augmented skillbook from natural-language corrections, clustering feedback across users and tasks into generalized skill templates that a neuro-symbolic policy can retrieve at run time.

TEA Lab starts at Virginia Tech

Fri, 01 Aug 2025 00:00:00 +0000

TEA Lab starts at Virginia Tech!

Best-paper award at the Generative Models x HRI Workshop @ RSS 2025

Sun, 15 Jun 2025 00:00:00 +0000

We received the best-paper award at the “Generative Models x HRI Workshop @ RSS 2025” for our work on “Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration”

Best-paper award at the Nonverbal Cues Workshop @ ICRA 2025

Tue, 10 Jun 2025 00:00:00 +0000

We received one of two best-paper awards at the “Workshop on Nonverbal Cues for Human-Robot Cooperative Intelligence at ICRA 2025” for our work on “Let Me Help You! Neuro-Symbolic Short-Context Action Anticipation”

Adaptation

Tue, 19 Mar 2024 00:00:00 +0000

Hybrid Models

Tue, 19 Mar 2024 00:00:00 +0000

Robotics

Tue, 19 Mar 2024 00:00:00 +0000

Assistant Professor

Mon, 01 Jan 0001 00:00:00 +0000

Bio

I am an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech, where I lead the TEA Lab. In my research, I aim to create intelligent robots and AI systems that are capable of seamlessly integrating with human environments and tasks. To this end, I develop neuro-symbolic methods that reason over the attributes and affordances of objects in the environment, allowing them to learn behaviors efficiently and adapt to new environments. My work spans robot learning, robot manipulation, human-robot interaction, and language- and vision-conditioned policies for robots that learn continually over their lifetime. I earned my Ph.D. from Arizona State University under Prof. Heni Ben Amor in the Interactive Robotics Lab, where I specialized in physical human-robot interaction. I’ve also collaborated on projects with Bosch, Intel AI Labs, and X, The Moonshot Factory.