Projects
Here are my most significant and recent projects. Check out my GitHub to see the source code and documentation for these projects and more.
Class projects will not be publicly visible on GitHub/GitLab/etc.
Artificial Intelligence Class Projects
Aug. 2022 – Dec. 2022
- Implemented IDA* to efficiently search for a path through a maze in OpenNERO in Python.
- Experimented with and iterated upon Neural Network design to predict COVID-19 cases given timeseries data.
- Developed Neuroevolution algorithms to prescribe actions to minimize COVID-19 cases, given historical data.
- Trained Reinforcement Learning algorithms to play a 3D first person shooter game.
Music Marketplace
Aug. 2022 - Dec. 2022
- Designed a full stack web application to connect music students with tutors.
- Website utilizes JavaScript and Bootstrap for the front end and Flask, SQL, and AWS for the backend.
Operating Systems Class Projects
Aug. 2021 – Dec. 2021
- Built a shell application to parse command-line Linux arguments and manage processes in C.
- Added threading, system call, virtual memory, and file utilities to the Pintos operating system using C.
Robot Learning Class Projects
Jan. 2021 – May. 2021
- Employed AI techniques to perform robotic tasks in simulation involving grasping and vision.
- Achieved high accuracies of 80%+ with Regression/Neural Networks using Scikit-Learn and PyTorch.
Computer Architecture Class Projects
Jan. 2021 – May. 2021
- Built a command-line interpreter in C for the Expression Evaluation Language (EEL).
- Developed a dynamic memory allocator in C to emulate ‘malloc’ and ‘free’ in the C standard library.
- Designed a simulator in C capable of executing assembly following Y86-64, a subset of the x86-64 architecture.
Weather Prediction
Jun. 2020 – Jul. 2020
- Developed a Python CLI program to generate a 48 hour weather forecast given the past 120 hours of data.
- Applied time series modeling to form a temperature curve that accurately reflects past data.
Rouse Robotics Scouting App
Sep. 2019 – Feb. 2020
- Authored a web application to automate data gathering at robotics events using JavaScript, HTML/CSS, and Jekyll.
- Enabled both offline and online data aggregation for 50+ teams per event.