I’m currently a third year Computer Science student at the University of Waterloo and am passionate about all things software, especially machine learning and artificial intelligence. Through multiple internships, I’ve had the opportunity to develop software in a variety of environments for many projects. Currently working on turning a Kia Soul into a fully self-driving car with WATonomous.
Skills
Languages: Python, C/C++, C#, HTML/CSS, SQL, R, Bash, Javascript
Frameworks: ROS, AWS, .NET, Selenium
Tools: Docker, Git, GitHub, Jenkins, JIRA, Linux, Solidworks
Libraries: Pandas, NumPy, PyTorch, Matplotlib, Slash, Scikit-Learn
Work Experience
Cloud Database Engine Developer
May 2025 - Aug 2025
SAP
Python Developer
Sep 2024 - Dec 2024
Burkett Statistical Consulting
- Used Pandas for data processing of utility meter data, producing a 90% smaller clean dataset
- Engineered features for EV load prediction and fitted numerous machine learning models achieving 80% accuracy
- Automated assembly line scheduling using Google OR-tools, Python and R, reducing manual effort and achieving a potential 5% reduction in production costs while meeting all production constraints.
WiFi Software Test Developer
Jan 2024 - Apr 2024
Ford Motor Company
- Implemented and tested Python automation test scripts, using the Slash testing framework, for in-vehicle WiFi connectivity modules extending test coverage to new hardware automating 10% of manual testing
Junior Data Scientist Intern
Jul 2023 - Sep 2023
Exponential Exchange
- Scraped price history of over 30 major market indices using Selenium and Python for data analysis
- Used Snowflake and SQL to compute correlations and created an interactive dashboard in Looker to visualize and compare the different indices
Junior Software Engineer Intern
May 2023 - Aug 2023
Inwards Inc.
- Upgraded company website using HTML/CSS, JavaScript & PHP, adding pages and improving load times by 50%
resume
Projects & Other Experience
Robotics & RL Researcher
October 2023 - Present
Autonomy Research Group - WATOnomous
- Conducted an in-depth literature review on both classical and deep-learning based (RNN, LSTM, Bi-LSTM with attention, etc.) Driver Intention Inference schemes and synthesized findings
- Adapted Hybrid Policy Optimization algorithm to use MPC demonstrations to guide reinforcement learning
- Wrote custom SAC implementation in PyTorch to get baselines for experimental validation
Autonomy Software Lead
October 2023 - Present
WATOnomous
- Used Docker, CARLA and ROS2 to leverage in-house HPC cluster for high-fidelity AV simulation
- Led team of 10 in development of ROS2 nodes for various world-modeling solutions for autonomy stack