I am a Ph.D. student at GRASP Lab, University of Pennsylvania, advised by Prof. Nadia Figueroa. I want robot manipulation policies that are interactive and scalable. To get there, I have worked on data-efficient learning, learning beyond teleoperation, and force-aware manipulation. I am also passionate about designing innovative hardware.
Before coming to Penn, I received my MS in Robotics from Northwestern University and BS in Aerospace Engineering from UIUC.
May 2026 - Joining Dyna Robotics as a Member of Technical Staff Intern.
May 2026 - Invited talk on Flow with the Force Field at Nvidia Dex Team.
Feb 2026 - Flow with the Force Field is accepted to ICRA 2026.
Feb 2026 - VPP is accepted to ICRA 2026.
Jan 2026 - VLMgineer is accepted to ICLR 2026.
Sep 2025 - Joining Amazon Robotics as an intern working on Vulcan Stow.
Jun 2025 - EMP is accepted to IROS 2025.
Jun 2025 - OCR is accepted to IROS 2025.
April 2025 - Presented as a spotlight speaker at the ICRA 2025 Doctoral Consortium.
April 2025 - EMP is accepted as a spotlight paper @ Workshop on Structured Learning, ICRA 2025.
In Submission
Workshop on Manipulation Robustness: Towards Human-Level Robustness under Real-World Challenges, ICRA 2026
We present a pipeline that jointly leverages generated video and audio to recover both motion trajectories and contact force profiles from a single task description, enabling zero-shot force-aware manipulation where a kinematic-only baseline fails.
ICRA 2026
Workshop on Contact and Impact-aware Manipulation, IROS 2025
Workshop on Exploring the Role of Energy in Robot Learning and Control, IROS 2025
We introduce a framework for generating force-informed data in simulation, instantiated by a single human demonstration, and show how coupling with a compliant policy improves the performance of a visuomotor policy learned from synthetic data.
ICLR 2026
Workshop on Robot Hardware-Aware Intelligence, RSS 2025
We introduce VLMgineer, a novel VLM-driven evolutionary framework that automatically co-design tools and actions to solve robotics task.
ICRA 2026
Best Paper Award at Workshop on Exploring the Role of Energy in Robot Learning and Control, IROS 2025
Best Student Paper Award at Workshop on Building Safe Robots, IROS 2025
A quadratic programming-based control framework enforces viability theory constructed constraints on a passive controller tracking a dynamical system, ensuring the robot states remain within the safe set in an infinite time horizon.
IROS 2025
Spotlight Paper in Workshop on Structured Learning for Efficient, Reliable, and Transparent Robots @ ICRA 2025
A one-shot stable imitation learning framework that allows robots to adjust their behavior based on the scene change while respecting the task specification.
ICRA 2025
We introduce MORF, a magnetic origami system enabling repeatedly reprogrammable, rigid structures ideal for adaptive robotic tools.
IROS 2025
Spotlight Paper in Workshop on Lifelong Learning for Home Robots @ CoRL 2024
A vision-based object-centric recovery policy framework that guides the system back to the training distribution in OOD situations without relying on extra data
ICRA 2024
A novel control architecture that allows a torque-controlled robot to guarantee safety constraints such as kinematic limits, self-collisions, external collisions and singularities and is passive only when feasible
ICRA 2024
This approach learns a motion plan with Neural Ordinary Differential Equations while guaranteeing stability and safety with Control Lyapunov Functions and Control Barrier Functions
RSS 2024
A dynamical system based representation for intent estimation with constraints in human robot co-manipulation tasks
CoRL 2023
A dynamical system based motion policy LfD method with stability guarantees that can generalize to new task configurations without new demonstrations
RA-L
A novel statistical model that applies the Riemannian metric on the n-sphere to efficiently blend non-Euclidean directional data with Euclidean states for learning stable, time-independent motion policies
Using maximum entropy deep IRL to learn agent preference in continuous environment path planning
Developed software and hardware pipeline to play yoyo with visual feedback control on the Sawyer Robot arm
Performed receding horizon control using data-driven approach with small data in a continuous space