• Accelerated particle track construction in collision experiments by optimizing a depth-first search (DFS) algorithm• Implemented and integrated the hardware-accelerated algorithm in C using Vitis HLS for FPGA deployment• Achieved a 10x speedup in matrix multiplication latency through array partitioning, pipelining, and loop unrolling optimizations

• Used Q-Learning and Deep Q-Learning algorithms to implement the Mountain Car environment in OpenAI Gymnasium• Successfully fine-tuned parameters like epsilon decay value to optimize each episode time during the hyperparameter optimization phase• Presented at the 2024 CRNCH Summit hosted by advisor Dr. Jeffrey Young in a poster session