I'm a proficient and enthusiastic application builder. I'm passionate about optimization, automation, and statistics-driven decision-making. Opening doors recently unlocked by AI.
Current AI | Walleye Capital
March 2024 - Present
Drove product end-to-end, from ETL to UI. Deployed bulk ingestion pipelines for millions of records per day; managed event-handlers for each record to reach users; designed customer-facing features.
Grounded generative AI in software best practices. Evaluated and tuned workflows for structured extraction and generative prose. Built a robust named entity resolution service. Combined ranking, chunking, and retrieval strategies to identify and generate content about developing trends in real-time.
Innovated on tooling. Used a custom agentic loop to generate thousands of unique scripts that scrape high-quality structured data (without AI) from different websites each day.
Centered software rigor. Maintained high test coverage for backend and frontend code in Python and Typescript, and extended testing paradigms to evaluate non-deterministic AI features.
Capsida Biotherapeutics, Inc.
January 2022 - March 2024
Led widely-used internal software platform (AWS+React+Django) providing: customized genomic design tools; long-running bioinformatics pipelines; scheduling automation and visualization; executive BI analyses; automated handoffs across platforms; integrations with lab robots; IP-related data mining. Onboarded cross-functional contributors, maintained testing suite, documented, and socialized tools.
Automated lab data plumbing by connecting platforms including: lab information database (Benchling), project management software (Smartsheet), and networked lab instruments. Built a QR-based inventory update system. Fully automated several lab instrument data ingest operations.
Developed forecasting models for primate immunogenicity, with a decision-support tool that anticipates spontaneous interruptions to animal availability (a widespread challenge in biotech). Built automated analysis pipeline that delivers increasingly precise recommendations to decision-makers as new assay results are recorded in lab information database. C suite relied on forecasts for (expensive!) contracts.
Anderson School of Management, UCLA
2020 - 2021
Taught "Data and Analytics" to students in the MBA programs as part of PhD track teaching requirements.
Created (great) statistics course materials with a JupyterHub/git-based deployment pipeline. Students clicked a "magic link" to access cloud-provisioned, SSO-enabled compute environments.
Sinai Temple
2018, 2019
Automated and optimized scheduling Bar/Bar Mitzvah dates for ~130 students via mixed-integer linear programming.
GroupThere - grouptherenow.com (offline)
2017 - 2020
Launched a carpool optimization tool for organizations. Minimizes total drive-time sum across groups of 2-100.
LA Community Action Network
2017
Re-implemented LAPD's "hotspot" generation algorithm. Compared hotspots to historical arrest/citation/crime report data from City of Los Angeles. Contributed results to community-generated report "Predictive Policing in Los Angeles".
FactoryOfEverything
2016 - 2017
Developed a model for purchasing, production, shipping, and holding over a factory-warehouse-retail system. Forecasting using classical signal processing, regression, and machine learning. Implemented MVP in MATLAB.
MS - Operations Research. GPA 3.94
2019-2021
BA - Mathematics, Computer Science minor. GPA 3.63
2010-2014
Awarded "Llewellyn Bixby Mathematics Prize" 2014: to the student with highest achievement in the Mathematics dept.
Anderson School of Management, UCLA
2021
Optimizes decisions that affect compartment flow parameters in discrete-time SIRD disease progression model.
Anderson School of Management, UCLA
2020
Extends strategies for algorithmic fairness from machine learning community to resource-allocation optimization setting.
Department of Mathematics, Pomona College
2014
Formalizes connections between Boltzmann Machine Distribution and unsupervised learning via sparse coding.
University of Minnesota, Minneapolis
2013
Unsupervised anomaly detection in video data using dictionary learning and sparse coding. An NSF-funded REU.
Awarded "Outstanding Presentation Award" at Joint Mathematics Meeting, 2014: top 15% undergraduate groups.