Available for Summer 2027 internships

Hi, I’m Ken
I build rigorous systems for
machine learning and quant.

CS undergrad at Columbia (Egleston Scholar, top 1% of class, GPA 3.76). IEEE-published in deep learning, USACO Platinum perfect score, and currently a Software Development Engineer intern at Amazon (SCOT), building a centralized business config service for the teams behind MOSAIC— Amazon’s unified topline, cube demand forecast, and related forecasting services. Fluent in Python and C++; love tough puzzles.

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Columbia UniversityB.S. Computer ScienceStatistics minor · GPA 3.76 · Expected May 2028CourseworkData Structures and Algorithms · Artificial Intelligence · Advanced Programming in CLinear Algebra · Probability Theory · Linear Regression · Multivariable CalculusBased inNew York, NYOpen to internships, research, and builder teams, including roles outside the New York area.

About

A bit about me

I’m a Computer Science student at Columbia, focused on machine learning, quantitative finance, and the systems that hold them up. I like problems where the math, the model, and the infra all have to agree.

This summer I’m a Software Development Engineer (SDE) intern at Amazon, on the Long-Term Planning and Forecasting (LTPF) team in Supply Chain Optimization Technologies (SCOT). Alongside that I build Quantiv, an options-implied earnings platform on Vercel: multi-week calendar, screener, symbol pages, and a Clerk watchlist over nightly JSON, with LightGBM scoring on DuckDB / Parquet and live quotes through Upstash.

Before that I published single-author at the IEEE ITSC on graph-network traffic forecasting (24% RMSE win over STGCN), earned USACO Platinum with a perfect Gold score, and built a CFD + neural-net F1 wing optimizer.

Toolbox

Languages

PythonTypeScriptC++JavaGoSQL

ML / Data

PyTorchLightGBMXGBoostScikit-learnDuckDBPandasPostgres

Systems

Next.jsFastAPINode.jsREST APIsRedis

Cloud / Infra

AWS (EC2, S3)DockerKubernetesTerraformCI/CDBash / Linux

Projects

What I've worked on

Apps in production, papers that have been published internationally, and competitions I'm still proud of. Look here to see what I built, what I used, and what I learned.

Quantiv

Jul 2025 - Present

Founder and Lead Software EngineerQuantiv · Options-implied earnings analyticsNew York, NY, USA · usequantiv.com

Founder and lead engineer on Quantiv: a Next.js dashboard for options-implied expected moves around earnings (multi-week calendar, screener, symbol detail, Clerk watchlist). The UI ships on Vercel from prebuilt JSON; a Python pipeline (DoltHub + Finnhub/FMP earnings, DuckDB over Parquet, LightGBM v3) refreshes nightly via GitHub Actions.

Live on usequantiv.com with nightly CI data refresh, Finnhub/Alpaca/Polygon quote overlay, and optional Railway FastAPI for live ML re-inference.

0.00B+option records

Dailynightly pipeline

Livequote overlay

Visit usequantiv.com

Publications

Papers and writing

Peer-reviewed and competition-published research.

Highlights in Science Engineering and TechnologyMay 20232citations

A Need For Speed: Enhancing F1 Race Cars with a Novel Computational Fluid Dynamics and Machine Learning Method

IEEE Intelligent Transportation Systems Conference Proceedings 2023September 20231citation

GC-INF: A Novel Adaptive Traffic Control System using Machine Learning for Turning Ratio Predictions

Contact

Let's talk

Open to internships, collaboration, or a quick coffee chat.

Hi, I’m Ken —I build rigorous systems for machine learning and quant.