Machine Learning Intern at A*STAR SIMTECH
Developed time series forecasting models on NHITS and TFT architectures, improved accuracy by 30% Finetuned TimeGPT and Chronos LLMs for feature reduction, decreasing computation time by 40%
Experiences
Software Engineering Intern at G LNK (YC W24)
Designed a robust CV extraction pipeline with Reducto, reducing customer intake time by 60% Constructed an end-to-end automated report generation tool for pharmaceutical ingredient analysis
Machine Learning Intern at Fermi National Lab
Extended recurrent convolutional neural networks (RCNN) for surface code quantum error correction Tuned RCNN model to achieve equivalent performance with less than 25% of original parameter count Quantized TensorFlow dense models with hls4ml for use in dedicated FPGAs, reducing load by 50%
Department of Energy Research Intern at Argonne National Lab
Utilized retrieval augmented generation with agentic LLMs to generate 200+ multiple choice Q&As Automated Q&A generation and verification pipeline with over 95% efficacy for the Aurora GPT Developed a tutorial on agent-based LLMs using AutoGen and LangChain for over 50+ instructees
Pritzker School of Molecular Engineering Student IT Worker
Handle software implementation and cleaning for over 100+ Linux, Mac, and Windows systems Designed backend automations to handle data entry tasks, boosting team efficiency by 30%
UChicago Open Data Project Member
Helped develop a Python program that collected internet speeds throughout Hyde Park using Ookla’s API and projected them onto a map through GeoPandas to see differences in internet accessibility throughout the neighborhood