Background

Education

Ph.D. in Computer Science, University of Illinois Urbana-Champaign
Expected May 2029
Advisor: Prof. ChengXiang Zhai

B.S. in Computer Science, Cornell University
May 2023
Cum Laude with Honors in Computer Science
Minor in Philosophy
Humanities Scholar, LSAMP Scholar

Research Experience

Research Assistant, University of Illinois Urbana-Champaign
January 2024 - Present
Advisor: Professor ChengXiang Zhai
Project: “Hypergraph of Text for Structuring Document Collections”

SPI Fellow, University of Illinois Urbana-Champaign
May 2023 - August 2023
Advisor: Professor Tandy Warnow
Title: “Community Search in Large Networks: Evaluating the State of the Art”

• Designed and ran experiments evaluating k-core and k-truss community search algorithms
• Presented Findings at Illinois Summer Research Symposium

Senior Thesis, Humanities Scholar Program, Cornell University
August 2022 - May 2023
Advisor: Professor Malte Ziewitz
Title: “Exploring the Practice of Ethics by Machine Learning Practitioners in the Tech Industry”

• Conducted hour-long semi-structured interviews with 10+ Machine Learning Professionals
• Presented findings at Humanities Scholars Undergraduate Research Conference

Undergraduate Researcher, Cornell University
Fall 2021 - Spring 2023
Advisor: Professor Chris De Sa
Project: Pruning Transformers with Interpolative Decompositions (Fall 2022 - Spring 2023)

• Ran experiments testing ID pruning on LLMs such as BERT with various NLP tasks
• Experiments led to conference submission

Project: Pruning CNNs for Transfer Learning (Spring 2022 - Summer 2022)

• Ran experiments testing Interpolative Decompositions pruning in transfer learning domains
• Developed code allowing an iterative pruning process, an approach matching S.O.T.A performance

Project: MCMC Neural Net Quantization (Fall 2021 - Spring 2022)

• Ran experiments testing Gibbs sampling quantization on ResNet/Cifar10
• Developed code allowing for more accurate replication of training parameters specified in original ResNet paper

Teaching Experience

Teaching Assistant
Advanced Information Retrieval, CS 510
University of Illinois Urbana-Champaign, Spring 2025

Teaching Assistant
Text Information Systems, CS 410
University of Illinois Urbana-Champaign, Fall 2024

Teaching Assistant
Introduction to Machine Learning, CS 4780
Cornell University, Fall 2022, Spring 2023

Professional Experience

Software Engineering Intern
Talroo, Austin, TX (Summer 2025)

• Built distributed web crawling system using Apache Spark and Delta Lake to extract job postings from company career pages, achieving 18x performance improvement through async processing and intelligent load balancing
• Designed three-tier adaptive extraction pipeline (HTTP → Browser LLM) with quality-based routing, achieving 94% recall accuracy on real-world validation tests against manually verified job counts
• Implemented distributed LLM request coordination system using Redis and Weighted Least Outstanding Requests algorithm, enabling zero rate-limit errors across multiple AI providers (OpenAI GPT-4, Google Gemini)
• Developed BERT classifier achieving 96% F1 score for job/non-job filtering to replace expensive LLM calls, significantly reducing API costs
• Created comprehensive robots.txt compliance system ensuring ethical crawling practices and sustainable long-term data access

Core Data Infrastructure Software Engineering Intern
Asana, Virtual Internship (Summer 2021)

• Completed in-depth data quality analysis enumerating benefits and ensuring safety of using new event logging code in production
• Prototyped logging for isolated spark clusters
• Created dataset size extractor for physical and external tables in order to expose dataset size to dataset consumers

STEP Intern
Google, Virtual Internship (Summer 2020)

• Collaborated with experts to research best methods for user embedding for our context
• Developed backend to web app feature allowing users to assess over and under-provisioning of a resource given some access management rule
• Rules were parsed and represented as an abstract syntax tree allowing for future rule optimization
• Created various utilities to help with data analysis including an efficient external sorting algorithm allowing for the sorting of datasets too big to fit into memory

Deep Learning Engineer - Intern
CACI International, Tampa, Florida (Summer 2019)

• Created new evaluation tools for computer vision experiments with added metrics
• Created script for building ImageNet into COCO style detection dataset
• Built tools to simulate low-shot learning on a full dataset
• Created Docker image to streamline usage of TensorFlow Object Detection API

Junior Research Scientist
CACI International, Tampa, Florida (Summer 2018)

• Researched the effect of class grouping on the performance of object detectors
• Experimented with many different architectures such as SSD, Faster-RCNN, and RetinaNet
• Built multiple datasets with different class groupings
• Modified dataset building script to allow for continuous writing decreasing memory usage substantially

Honors and Awards

• NSF GRFP (Spring 2025)

Involvements

Co-Organizer, TREC 2025 Product Search and Recommendations Track

• Wrote and documented baseline results for product search task