Aman Arora

Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications.

• PhD in Computer Science from The University of Texas at Austin

Research interests emphasize domain-specific acceleration through FPGA optimization, compute-in-memory architectures, and machine learning for CAD/EDA. His work addresses critical challenges in energy efficiency and throughput for AI workloads.

Recent publications demonstrate trends toward compute-in-memory systems, FPGA-based deep learning acceleration, and sustainable hardware design. Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization.

• Laboratory Website: ADVENT Lab

Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.