My Projects

I've built a few side projects in the past few years while I was not doing research, working on my startup, or school. I plan on adding more here frequently.

GPTHunt

December 2023

I created the ProductHunt for GPTs. Users can list and upvote their favorite GPTs. I believe that this method of searching for and ranking GPTs is better than a generic store, considering that GPTs are much easier to build than apps or products. This was more for me to learn how to build a web app with auth and storage.

GPTHunt Image
Tech Stack

GPU Puzzles - C++ Edition

October 2023

I created a C++ version of Professor Sasha Rush's GPU Puzzles. These puzzles were originally in Numba, but I converted them to C++ kernels and wrote the kernel invocation block. These puzzles consist of common building blocks such as prefix sums, 1d and 2d convolutions, and matrix multiplication.

GPU Puzzles Image

Duke Organizations

2020-2024

  • Duke Innovation Studio: First cohort and advisor to Kora, a medical device company building surgical lamps and tools
  • Duke BMES: Industry and Alumni Lead - organized a panel for students to talk about summer internships in tech and consulting
  • Duke Science Olympiad: Event supervisor and test writer

LectureChat

October 2023

I built an app that allows anyone to upload a lecture video in any language and talk with it in any language through voice and text. The app uses AI to generate a transcript in the native language and then allows the user to pick any language to translate it into. Furthermore, the AI creates quizzes based on the transcript in any language and interacts with the user via text and voice. Project submitted to Duke Generative AI Hackathon. Built in 2 days.

LectureChat Image
  • Built using NextJS, Deepgram's speech-to-text APIs, OpenAI's GPT-3.5, and Redis
  • Built with Cursor and GPT-4 assistance for hackathon speed
Tech Stack

Body Part X-Ray Classifier

2022

I created a classifier for body part X-rays (using a CNN). It contained 22 classes of body parts and a massively imbalanced dataset, so we reduced the amount of data for over-represented classes. The goal was to analyze the convolution layers of the CNN to determine the types of filters (low-pass, high-pass, band-pass, band-stop, etc.).

CNN Image
  • Built with PyTorch, simple CNN with a few convolution layers, max-pool, and Adam optimizer
  • Analyzed the resulting trained filters to see what types of filters were learned
Tech Stack

Coronavirus US Case Updates

March 2020

I created a webscraper with Slack webhooks to periodically send US coronavirus daily case updates to my family's Slack channel. It tracked the total number of cases in the US, total number of cases in California, total number of deaths at the nation and state levels, and percent increase day-by-day of both deaths and cases.

Tech Stack

Brainee

May 2019 - January 2020

At the Human Technology Interaction Lab in the University of Alabama's Computer Science department, I developed a browser-based platform to allow researchers of all backgrounds to run large-scale EEG-based experiments on the human brain, using the Muse EEG headset. We use the Muse EEG headset as a fast bluetooth enabled EEG device that streams data to the browser, pre-processing algorithms that include combinations of low and high pass filters to clean the data, and post-processing algorithms such as LDA to discern motor movements.

Brainee Image
Tech Stack