I am a Computer Engineering Ph.D. student at Purdue University, specializing in Systems for Machine Learning. My research at the Dependable Computing System Lab focuses on optimizing large language model (LLM) inference on GPU clusters and developing efficient AI solutions for resource-constrained embedded devices. During my internship at Futurewei Technologies, I worked on agent memory architectures and planning.
📰 News
May 2026
I will be joining Nokia Bell Labs as an AI/ML system research intern in Murray Hill, New Jersey!
May 2026
Our paper Embodied Task Planning via Graph-Informed Action Generation with Large Lanaguage Model is accepted to 43rd International Conference on Machine Learning (ICML 2026)!
🎓 Education
- Ph.D. in Computer Engineering, Purdue University, 2021 – Present
- B.S. in Computer Engineering (with Distinction), Purdue University, 2019
💼 Professional Experience
ML Algorithm Intern, Futurewei Technologies, San Jose, California
Sept 2025 – Dec 2025
ML Research Intern, Houston Methodist Research Institute, Houston, Texas
May 2023 – Aug 2023
Software/Control Engineer, Cummins Inc, Columbus, Indiana
June 2019 – July 2021
📚 Publications
Deep-Reproducer: From Paper Understanding to Code Generation
Neurips@DL4C, 2025
Ascendra: Dynamic Request Prioritization for Efficient LLM Serving
arXiv Preprint, 2025
HopTrack: A Real-time Multi-Object Tracking System for Embedded Devices
arXiv Preprint, 2024
Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks
arXiv Preprint, 2024
DAG-based Task Orchestration for Edge Computing
41st International Symposium on Reliable Distributed Systems, Vienna, Austria, 2022