Research Experience

Google Scholar

Interested in embodied real-time intelligence. My collaborators and professors are great! :)

Robot Teaching & Teaming Lab | Undergraduate Researcher

• Research under Prof. Mike Hagenow
• Built 80 Hz joint-velocity controller and custom IK stack used by 11 lab researchers (Nix deployment)
• Engineered 80 Hz data pipeline streaming RGB, point clouds, and robot state with Foxglove visualization
• Architected lab-wide policy training infrastructure for 3D Diffusion Policy, π_0.5, and Diffusion Policy
• Trained real-time collaborative policies for assembly (handover, turn-taking); designed fixtures in Onshape
• Developed teleoperation system supporting Xbox, SpaceMouse, and force inputs for demonstration collection
• Achieved 2× faster robot execution via high-gain control and mid-trajectory sampling
• Profiled training with Nsight Systems; developing custom CUDA kernels to accelerate inference sampling
• Submitting paper to CoRL 2025

ADAPT @ UIUC | Undergraduate Researcher

• Research under Prof. Charith Mendis
• Desugared 46 TASO rewrite rules into XLA-HLO in TensorRight for rank-polymorphic verification
• Expanded DSL with rank lower-bound constraints to enable both rank monomorphic and polymorphic verfication

Stewart Lab @ Morgride Institute for Research | Research Intern

• Supervised under Ron Stewart @ Morgridge Institute for Research
• Published paper in BMC Bioinformatics
• Combined biomedical literature-based discovery with LLM hypothesis evaluation (feel free to play with it here)
• Fine-tuned custom LLM for biomedical text analysis with synthetic data (8,600+ downloads on Huggingface!)
• Improved accuracy of RAG relevance filter from 70% to 90% with NEFTune and RsLoRA
• Deployed custom LLM on university HPC with Nvidia Container Toolkit + Docker & Paramiko
• Sped up internal analysis pipeline by 15x with batching + VLLM

Susceptibility of Adversarial Attacks on Medical Image Segmentation Models | Independent Publication in High School

• Self published at IEEE's 2023 International Symposium on Biomedical Imaging (ISBI) conference. I got cited twice! 🎉
• Explored the efficacy of adversarial attacks on SOTA image segmentation models (UNet, UNet++, UNet + ResNeXt-101 backbone, UNet + EffNet-B7 backbone)
• Discovered that varying the loss used in FGSM improved Attack Success (defined in paper)

Deeply Supervised Transformer Encoders | Independent Research in High School

• Supervised under Prof. Mohammad Taher Pilehvar @ University of Cambridge
• Examined the application of UNet++ style deep supervision in transformer encoders, which unfortunately didn't work very well :(
• Adding Deep Supervision increased BERT accuracy by 5% on the WNLI benchmark

Home