Akhilesh Jaiswal

Dr. Akhilesh Jaiswal serves as Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison, where his research pioneers device-circuit co-design for next-generation computing systems. His work focuses on enabling extreme-edge intelligence through processing-in-pixel technology, in-memory computing architectures, and bio-inspired neuromorphic systems.

His academic credentials include:

• PhD in Nano-electronics from Purdue University (2019)
• MS from the University of Minnesota (2014)
• Bachelor of Technology from Shri Guru Gobind Singhji Institute of Engineering and Technology (2011)

Dr. Jaiswal's research program centers on revolutionizing edge computing through hardware innovations that integrate sensing and processing. His device-circuit co-design approach leverages alternate state variables to create energy-efficient systems for real-time applications, with particular emphasis on retina-inspired sensors and photonic memory architectures. This work bridges semiconductor physics with AI acceleration needs, targeting applications from autonomous systems to biomedical devices.

Analysis of his 2023-2025 publications reveals dominant themes in photonic SRAM-based in-memory computing (40% of output), retina-inspired motion processing (30%), and secure hardware architectures (20%). His team consistently develops novel bitcell designs that enable XOR logic execution within memory arrays while maintaining compatibility with CMOS fabrication processes. Recent work shows increasing focus on biomedical applications of processing-in-pixel technology.

His distinguished recognition includes:

• Three consecutive ISI Exploratory Research Awards (2020-2023)
• IEEE Brain Community Best Paper Award (2022)
• 27 issued US patents with multiple pending applications
• Nomination for USC Moore Inventor Fellowship (2022)

Dr. Jaiswal actively mentors graduate researchers through ECE 790/890/990 courses while securing exploratory funding through ISI and Keston Foundation awards. His patent portfolio demonstrates exceptional translational impact, with industry game-changer classifications from USPTO. The 2022 VLSI-SoC nomination and multiple research highlights in major outlets validate his contributions to hardware security and neuromorphic vision sensors.

His laboratory develops integrated hardware platforms combining magnetic tunnel junctions, photonic memory, and CMOS image sensors to create unified processing-in-sensor systems. Current projects include retina-inspired motion segmentation for event cameras and electro-optic frequency transducers for quantum computing interfaces, with strong industry collaboration through patent licensing.