Hello! I’m Kenny, a versatile professional with a diverse background. Most recently, I worked at Jane Street in a Strategy and Product role, where I engaged in data analytics, project management, and daily problem-solving. At this leading quantitative trading firm, I regularly leveraged million-row datasets to produce value for traders and collaborated with teams across trading and sales on strategies for handling billions of dollars in trading capital.

I graduated from Princeton University in 2023 with a BSE in Operations Research and Financial Engineering, along with four minors in technical fields such as Statistics, Machine Learning, and Applied Mathematics. I also gained valuable experience through extracurricular projects in sports analytics and conducted research on advanced linear algebra techniques.

In addition to my academic pursuits, I’ve taken on several leadership roles, including serving as a DataDev subteam officer in the Princeton Data Science Club and as co-vice president of the Table Tennis Club.

In my spare time, I enjoy playing volleyball, exploring NYC’s hottest restaurants, and following football and basketball. Recently, I’ve also developed an interest in archery.

Feel free to check out my work below and view my resume here!


WAR in Pieces: A Bottom Up Approach to Player Evaluation in the NBA
Abridged poster version here; a novel bottom-up machine learning algorithm to quantitatively evaluate NBA players by estimating wins above replacement; Princeton University senior thesis completed under the guidance of Professor Ramon van Handel

Fast Covariance Estimation Techniques
Experiments for a fast estimation algorithm applying Principal Component Analysis and Fourier-Bessel basis functions to optimize Covariance Wiener Filtering in denoising cryo-EM imaging; reduced runtime from O(N) to sub-logarithmic time with 1.3% relative error; future work by advisor was published as Fast principal component analysis for cryo-electron microscopy images (Marshall et al., 2023)

What Makes Blocks Good? (2022)
A re-examination of the traditional defensive statistic of blocks by evaluating them using custom metrics that capture their indirect effects both within and after possessions in the NBA; builds on findings from previous work of A Study of the Goodness of Blocks (2021)

Predicting the String Played by a Cellist through Edge Detectors, Hough Transforms, and k-Nearest Neighbors (2021)
Final project applying computer vision techniques and a KNN machine learning model to determine which string is being played by a cellist based on visual data

NYC Trip Visualization (2022)
A fun gadget containing visualizations and summary of NYC summer trip spending


Data Analysis Projects

WAR in Pieces: A Bottom Up Approach to Player Evaluation in the NBA
Abridged poster version here; a novel bottom-up machine learning algorithm to quantitatively evaluate NBA players by estimating wins above replacement; Princeton University senior thesis completed under the guidance of Professor Ramon van Handel

What Makes Blocks Good? (2022)
A re-examination of the traditional defensive statistic of blocks by evaluating them using custom metrics that capture their indirect effects both within and after possessions in the NBA; builds on findings from previous work of A Study of the Goodness of Blocks (2021)

Free Agency and Triadic Closure (2021)
An analysis testing the applicability of triadic closure in using player attributes to predict NBA free agency decisions

Predicting Fast Food Growth (2021)
Final project using SVM and logistic regression to predict growth of fast food restaurants by locale in United States

A Study of the Goodness of Blocks (2021)
An evaluation of blocks and their value in the NBA

Load Management (2019)
A paper detailing original research regarding effects of load management on the NBA


Other Projects

Fast Covariance Estimation Techniques
Experiments for a fast estimation algorithm applying Principal Component Analysis and Fourier-Bessel basis functions to optimize Covariance Wiener Filtering in denoising cryo-EM imaging; reduced runtime from O(N) to sub-logarithmic time with 1.3% relative error; future work by advisor was published as Fast principal component analysis for cryo-electron microscopy images (Marshall et al., 2023)

Predicting the String Played by a Cellist through Edge Detectors, Hough Transforms, and k-Nearest Neighbors (2021)
Final project applying computer vision techniques and a KNN machine learning model to determine which string is being played by a cellist based on visual data

Perfect Games (2021)
A short analysis written for Harvard Sports Analytics Club to describe games in NBA history where players made all of their 2-point field goal attempts

Useless Benches in the NBA (2021)
An analysis of worst bench performances in NBA history


Datasets Created

NBA Possession Data (2022)
Individual possession data from all regular season games in 2021-22 season scraped using BS4

NBA Block Data (2021)
A summary of possessions involving a block from 1996-2020 scraping using BS4

NBA Game Data (2021)
Aggregated NBA box scores from 1996-2020 scraped using BS4

English Synonym Corpus (2021)
Ten synonyms for the 333,333 most common English words scraped using BS4


Personal Projects

NYC Trip Visualization (2022)
A fun gadget containing visualizations and summary of NYC summer trip spending

Battleship (2022)
A virtual version of Battleship board game created using React from scratch without tutorial

Greece Recap (2022)
A recap of family vacation from perspective of Smiskis

Unhelpful Thesaurus (2021)
A fun widget to generate nonsensical sentences based on synonyms scraped from thesaurus.com

24 Game (2021)
A customizable widget to solve 24 game using R Shiny

NFL Bet (2020)
A comprehensive analysis of year-long bet with friend regarding NFL game outcomes

Rubix Cube (2019)
A report on semester-long commitment to improve at solving a Rubix cube

Powerade (2019)
A fun visualization of Powerade addiction

First Point Analysis (2015)
A comprehensive analys– ok let’s be honest this was way before I learned anything about stats but I was somehow motivated to make this


Contact

I am actively seeking a full-time role and would love to connect. Please feel free to reach out to me at kenhuang [at] gmail [dot] com.

(Last updated October 12, 2024)