I am in the Engineering BMS – Runtime Frameworks team within the Engineering Platform, Infrastructure, and Common Services (EPICS) department.

I performed Energy-efficient Neural Networks with Low-precision Parameters by examining different optimization algorithms on GPU applications and neural networks to maximize energy savings while maintaining accuracy. I developed lab analytical skills with C, Python, and MATLAB programming. I proposed a method performing approximate detection and bypass of trivial computations for energy-efficient computing, called AxBy.