I've always been drawn to experiences that feel like magic. Whether it was watching my first firework show or someone pulling a quarter from behind my ear, I was always left thinking, "How on earth did they do that?"
Now, as an adult, I'm still amazed by the incredible innovations around us. I remember the first time I saw a driverless Waymo car go by, and once again, I found myself asking, "How on earth did they do that?" The magic of tech and machine learning is creating some truly awe-inspiring stuff.
Why Tech?
AI / ML +
Data Science
I get energized by building products that inspire awe on the surface while solving a deep-seated problem underneath.
Below are the building blocks that are paving my way to achieve this magic.
Featured
Computer Vision & ML Deployment | 🔥🌿💧🪨
This project tackles image classification of 151 original Pokémon using a convolutional neural network (CNN) and vision transformer (ViT) model on 10,000+ images. The fine-tuned model is deployed via a containerized RESTful API for real-time inference.
Cancer Genomics & Applied Machine Learning Research 🧬
This project combines differential splicing analysis and machine learning to explore pmCiC's role in tumor grade prediction. Aiming to uncover new insights into cancer metabolism and potential therapeutic targets.
🚧 CASE WRITE UP COMING SOON! 🚧
Building a Retrieval-Augmented Q&A System | 🤖
This project focuses on developing a state-of-the-art retrieval-augmented question-answering (RAQA) system. By integrating natural language processing (NLP) techniques with a transformer-based model, it leverages large-scale document retrieval and contextual embedding generation to provide accurate and relevant answers.
🚧 CASE WRITE UP COMING SOON! 🚧
Recommender System with Collaborative Filtering & ML | 🛍️
This project involves building a robust recommender system using collaborative filtering and content-based filtering algorithms. The system dynamically adjusts user preferences by analyzing historical data and fine-tuning latent factor models.
🚧 CASE WRITE UP COMING SOON! 🚧
BART Algorithm Analysis 🚉
This presentation explores the use of Neo4j NoSQL algorithms, particularly harmonic centrality and Louvain modularity, to optimize delivery logistics for a kitchen that produces and sells fresh-frozen meals and would like to expand leveraging BART partnerships.
NFL Offense Analysis 🏈🏆
Explore the intricacies of NFL strategies with the "NFL Offensive Play Analysis 2009 - 2017." This comprehensive report dives into eight years of play-by-play data, examining how offensive plays evolve over games and impact the final score!
Software Engineering (SWE)
Classic Pong 🏓
Rediscovering another timeless classic! Grab a friend and play against each other in "Pong".
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Snake Game 🐍
A revist to a classic! Love the irony of using Python code for a game called "Snake". Check it out!
Turtle Crossing 🐢
Be sure to look both ways and look out for cars as you crawl through traffic! Give it a try!
Research + Experiments
Researching biases in Large Language Models (LLMs) 🧠
This report investigates whether large language models (LLMs) exhibit biases when generating socio-economic data based on different racial identities. Using a standardized prompt and controlled variables, we analyze the potential disparities in LLM outputs. Explore our findings and the implications for fairness in AI.
Understanding Voter Difficulty by Party 🗳️
This report explores whether Democrats or Republicans experience more difficulties when voting, using survey data from the 2022 American National Election Studies. Dive into our detailed analysis and insights on this critical electoral issue.
🚧 Case write up coming soon! 🚧
Understanding the Influence of Socioeconomic Factors on Work Hours ⏰
This report delves into how age and factors such as education and marital status influence weekly work hours, aiming to inform policies that enhance work-life balance and productivity. Using data from the General Social Survey, we explore the dynamic relationship between these variables within the U.S. labor market.
🚧 Case write up coming soon! 🚧