Swarm User Interfaces, LLMs, Multi-modal Interaction
Motivation
This project explores what happens when hand-shaping and speech are combined for a tangible authoring method.
Inspired by Radical Atoms and Perfect Red,
this paper pushes towards visions of fluid, tangible interaction. This is a passion project that I presented at ACM UIST 2025 in Korea!
User manipulation-flexible locomotion using deep reinforcement learning.
Research In Progress
Progress Snapshots
Thus far, I have created an accurate MuJoCo simulation of our lab's flywheel hardware, with a simulated PID motor controller.
In this simulation, I have a decent PPO control policy that enables basic flipping, turning, and translational movement.
Early hardware testing for translational locomotion.
Policy learns to flip from horizontally-oriented flywheel to vertically-oriented flywheel (after 140k timesteps)!
Relevant Research Domains
Deep Reinforcement Learning, Self-Reconfiguring Hardware, Modular Robotics
Motivation
This project hopes to push forward research on self-reconfiguring, modular robotic systems,
such as M-Blocks.
My vision for this project is to allow users to assemble shapes with cube primitives, which
immediately know how to move based on a shape-flexible control policy. This control policy would also allow for
more flexibility in self-assembling robotic systems.
Skills Involved
Robotics simulation with MuJoCo, Reinforcement Learning, Hardware Design (PCB design, 3D modelling)
Next Steps
Improvements to RL policy.
Transition from MuJoCo simulation to hardware.
Exploration of multi-module locomotion. (Multiple modules attached together!)
Haptics Project [Under Review CHI 2026]
Hidden for now!
Research In Progress
Role
Working as a co-lead author on a haptics paper. Very excited about the project, but hidden for now!
Relevant Research Domains
Haptics
Skills Involved
3D Modelling, Electronics (PCB design, microcontrollers), Programming, Simulation
Video Learning Project [Anonymized]
Developing an autoencoder architecture for robot learning purposes.
Research In Progress
Role
Working under a PhD student, I have mainly contributed on dataloading pipelines for parallelized training on GPU, deploying RL agents for data collection, and visualizing autoencoder outputs during training.
Relevant Research Domains
Deep Learning, Computer Vision, Diffusion, Robotics
Skills Involved
PyTorch, CUDA
Motivation
Hidden for now!
Side Projects
GreenGuide
Grocery store item sustainability feedback through barcode-scanning glove.
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