I am an Assistant Professor of Computer Science at Kennessaw State Unviersity. I have completed my Ph.D. from the Department of Computer Science at UTSA, advised by Dr. Mimi Xie. Before joining academia, I spent five years in the software industry building backend systems and databases.

As learning model sizes growing faster than hardware efficiency improves, conventional computing architectures are becoming increasingly unsustainable. Rather than relying on ever-larger centralized hardware, I envision next-generation embedded systems that perform inference locally, operate on energy harvested from the environment, and remain secured.

Our research design inference algorithms targeting both von Neumann and non-von Neumann architectures. Specifically, we study neural network and hyper-dimensonal computing from a systems perspective, optimizing four aspects in resource-constrained environments: (1) memory, (2) computation, (3) energy efficiency, and (4) privacy.

Our research has appeared in venues such as ICCAD, DATE, IEEE TCAD, and ACM TODAES. I also serve on the Technical Program Committees (TPC) of DAC and MLSys and reviewer for IEEE TCAD.

Research Interests:

• Intelligence on and beyond the Edge
• Energy-Efficient Inference
• Privacy Preserving Inference

I always look for motivated PhD students. Stduents provding the evidence of genuine research interest will be prefered.