CV
TEST
Education
Ph.D. Candidate, Electrical and Computer Engineering
University of Illinois, Urbana-Champaign
Advisor: R. Srikant
Aug 2022 - May 2027 (Expected)
M.S., Electrical and Computer Engineering
University of Illinois, Urbana-Champaign
Aug 2017 - May 2019
B.S. with Highest Honors, Electrical and Computer Engineering
University of Illinois, Urbana-Champaign
Minor in Mathematics, James Scholar Honors Program
Aug 2014 - May 2017
Work Experience
Applied Scientist Intern
Amazon (Product Quality & Perfect Order Experience), Seattle, WA
May 2024 - Aug 2024
- Spearheaded an initiative to solve a critical data sparsity problem, developing a predictive satisfaction model from the ground up that expanded metric coverage from <5% to 100%.
- Owned the full project lifecycle, from problem formulation and data acquisition to building the final ensemble model (GBDTs & NN) using behavioral signals.
- The resulting satisfaction score was validated as a powerful feature, and its integration into production systems was greenlit for development.
Applied Scientist Intern
Amazon (Search Relevance), Palo Alto, CA
May 2023 - Feb 2024
- Designed a novel LLM tailored for semantic search ranking, which outperformed a highly-optimized production baseline with a ~1.2% relative lift in nDCG@1.
- Formulated a listwise ranking method for LLMs, enabling the model to evaluate the relevance of multiple products for an input query.
- Architected a scalable data pipeline on AWS to train LLMs on a massive corpus.
Advanced Research Team Lead and Researcher
VUNO Inc.
May 2019 - Aug 2022
- Led research on novel ML methods, resulting in first-author NeurIPS and AAAI publications.
- Promoted to Research Lead, setting the technical direction for the advanced research team and mentoring junior members.
- Contributed to the development and analysis of deep learning models across medical imaging modalities (Chest X-ray, CT, histopathology).
Cryptography Developer Intern
ICTK Holdings
June 2017 - Aug 2017
- Developed a lightweight Elliptic Curve Cryptography (ECC) library from scratch in C and Assembly, optimizing for low-latency and minimal memory usage on embedded systems.
Technical Skills
- Languages & Platforms: Python, C, Assembly, AWS (EC2, SageMaker)
- Libraries & Frameworks: PyTorch, HuggingFace, AutoGluon, Scikit-learn, Pandas, Polars
- Theoretical Foundations: Stochastic Optimization, Probability Theory, Active Learning, OOD Detection