Experience
RoboInvesting Member
GT Data Science Club
September 2025 – Present
More experience details coming soon...
Undergraduate Researcher
GT Automated Algorithm Design
January 2025 – Present
VIP Team Page- Minimized error by 20% and optimized model complexity by implementing genetic programming and multi-objective optimization, including symbolic regression and Pareto front analysis, by utilizing the DEAP Python library.
- Achieved greater accuracy than traditional ML models by leveraging NSGA-II selection and optimizing 92 generations, enabled by automating the machine learning algorithm design on the Titanic dataset.
- Facilitated 5 Monte Carlo trials to evaluate and score algorithm performance by enabling a local computer to function as a worker process within an evolutionary framework via a server connection through SQL.
Software Engineer
GT RoboJackets RoboCup
August 2024 – May 2025
- Integrated multi-agent adversarial strategies and enhanced motion planning algorithms for six autonomous soccer robots using C++ and ROS2 in an Agile team.
- Improved decision-making efficiency in the stack by optimizing robotic strategy through dynamically adjusting behavior in simulation using rqt.