Managed 3 competitive Valorant teams of 8 players each; organized tryouts, selected and onboarded players, and registered teams for tournaments and leagues
Planned and coordinated social events to foster team cohesion and community engagement
Developer Co-op
Equisoft
Philadelphia, USA
09.2023 - 03.2024
Executed targeted code modifications for XML and database management within a professional codebase
Gained hands-on experience writing and executing SQL commands for effective database interaction
Software Engineer – Content Development Team
NBME
Philadelphia, USA
09.2022 - 03.2023
Developed and maintained Java applications with Spring Boot framework, testing and refining programs to improve performance and functionality
Researched emerging technologies and software engineering best practices to inform and support development efforts
Software Engineer – Web Based Testing
NBME
Philadelphia, USA
09.2021 - 03.2022
Collaborated with Agile development team to build and maintain automated testing scripts in Java, enhancing testing efficiency
Updated code automation to integrate with new websites, validating functionality through comprehensive testing
Concepts: Reinforcement Learning, Deep Q-Network (DQN), Software Development, Software Testing, Database management, Test Automation, Agile methodologies
Projects
PokéDnD – Pokednd.live
Co-developed a full-featured web platform for a Pokémon-based tabletop RPG, handling character sheets, dice rolling, catching, trading, and a complete battle system
Translated the Pokémon video game battle system into a dice-based TTRPG format using each Pokémon's stats, abilities, and moves as the foundation for combat outcomes
Designed a character class system influencing battles via flat damage bonuses, additional dice rolls, power multipliers, and accuracy bonuses.
Pokémon RL Battler
Developed a Deep Q-Network (DQN) reinforcement learning agent trained across 20,000+ episodes on a university GPU cluster; achieved a 25% win rate against a max damage agent
Identified Q-learning's inability to generalize across the large state space and independently redesigned the agent using DQN via PyTorch for improved performance
Engineered and iteratively tuned a custom reward function with epsilon-greedy exploration strategy as primary developer on a 3-person team.
Senior Design – Cryptid Climb
Solely designed and implemented the core climbing mechanic for a 17-person senior design team, enabling players to reach, grab, and mantle surfaces
Built using UE5 Blueprints and inverse kinematics via Unreal's Control Rig; used mathematical calculations to determine body rotation based on hand placement and wall hold positions
Delivered entirely from scratch with no prior UE5 or animation experience.