About Me
I'm a UChicago graduate (2024) who studied economics and data science. I am now pursuing an MS in computer science at Columbia, where I am interested in leveraging graph representation learning & deep learning to better understand the brain and to enhance the communication process. My dream would be to enable the transfer of high dimensional information directly between humans, reaching a sort of advanced telepathy.
Featured Projects
Mechanistic Interpretability - Superposition Hypothesis
Project recreating Anthropic's "Toy Superposition" paper, showcasing how ReLU pins layer activation spaces to the "privileged" model neuron basis.
Skills: Python, PyTorch, Sparse AutoEncoder, Deep Learning
Mechanistic Interpretability - ResNet
Project exploring how a custom-trained residual CNN learns interpretable features and classifies images from the CIFAR10 dataset. Analyzed feature learning heirarchies and circuits through activation visualization.
Skills: Python, PyTorch, Feature Visualization, CNN, Residual Networks
Facial Tracking Research
A research project with the UChicago EMK Lab using geometric facial tracking meshes to analyze conversational facial interactions
Skills: Python, Data Preprocessing, MediaPipe, PCA
Andrej Karpathy Learning Series
A comprehensive series of projects following Andrej Karpathy's educational content, exploring deep learning fundamentals through hands-on implementation. Includes both the makemore language modeling tutorials and GPT implementation from scratch.
Skills: Python, NLP, Deep Learning, Neural Networks, Transformers, PyTorch, Attention Mechanisms
LLM Political Biases
A project fine-tuning LLMs on FOX/CNN data to explore ease of model biases.
Skills: Python, LLMs, Fine-Tuning
Other Projects
Retrieval Augmented Generation Demo
A project implementing a RAG framework for document information retrieval and synthesis.
Skills: Python, LLMs, RAG, LlamaIndex
Graph Neural Network
An exploratory GNN project analyzing the arxiv research paper dataset.
Skills: Python, PyTorch, PyTorch Geometric, Deep Learning, GNN
Neural Signal Clustering and Gaussian Mixture Models
A project exploring clustering methods on neural signal data such as KMeans and PCA-assisted KMeans. Additionally explores use of same techniques on mnist digits dataset.
Skills: KMeans, PCA, SVD, Neural Data
Image Compression and Dimensionality Reduction
A project exploring Singular Value Decomposition and its use in compressing image file sizes.
Skills: Python, Linear Algebra, SVD