CAnand Raghunathan, Silicon Valley Professor of Electrical and Computer Engineering

Anand Raghunathan, the Silicon Valley Professor in Purdue University's Elmore Family School of Electrical and Computer Engineering, has been honored with the IEEE Computer Society 2025 Edward J. McCluskey Technical Achievement Award. He is being recognized for his “pioneering contributions to the field of approximate computing and its application to the design of hardware for artificial intelligence.”

“I am deeply honored to be chosen to receive this award named after one of the true legends of our field – Ed McCluskey. I had the privilege of not only knowing him but also being part of his academic lineage,” Raghunathan said.

The Edward J. McCluskey Technical Achievement Award, presented annually, honors individuals who have made significant and innovative technical contributions to the field of computer engineering. Raghunathan's work in approximate computing has been instrumental in enhancing the efficiency and performance of hardware systems tailored for AI applications.

“Professor Raghunathan’s pioneering research in improving the efficiency of AI hardware — specifically, trained quantization of deep neural networks — has been foundational to enabling transformative advances in AI systems across the industry,” said Vivek De, fellow and director of circuit technology research at Intel.

Raghunathan is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). He received Purdue’s Arden L. Bement award and the Semiconductor Research Corporation (SRC) Technical Excellence award in 2024 for his contributions to AI Hardware. Raghunathan co-directs the SRC/DARPA funded Center for the Co-design of Cognitive Systems and is the founding co-director of the Purdue-led Center for a Secured Microelectronics Ecosystem.

“Anand has been at the forefront of research that is shaping the future of computing,” said Milind Kulkarni, Michael and Katherine Birck Head and Professor of Electrical and Computer Engineering. “His pioneering work in approximate computing has had a profound impact on the design of AI hardware, making computation more efficient and scalable. We are incredibly proud of his accomplishments and this well-deserved recognition.”