Yuhao Ju Receives IEEE SSCS Predoctoral Achievement Award
Northwestern Engineering’s Yuhao Ju has received a 2023 Predoctoral Achievement Award from the Institute of Electrical and Electronics Engineers (IEEE) Solid-State Circuits Society (SSCS).
Ju is a PhD candidate in computer engineering advised by Jie Gu, associate professor of electrical and computer engineering at the McCormick School of Engineering and director of the Very Large-Scale Integration (VLSI) Research Lab.
“Receiving this award holds immense importance to me on both a personal and professional level,” Ju said. “On a personal level, this award is a source of great pride and motivation. The recognition of the SSCS community provides me with the encouragement to continue pushing the boundaries of innovation in the solid-state and VLSI domains. Professionally, this award represents an important acknowledgement of my previous research in the solid-state field, which will also enhance my credibility and visibility within academic and industrial sectors.”
Predoctoral Achievement Awards are granted based on academic record and promise, quality of publications, and a graduate study program plan aligned with the SPSS charter to foster innovation and excellence in the design, implementation, and application of solid-state integrated circuits for applications including computers, communications, signal processing, and optoelectronics.
Ju’s research interests center on the development of domain-specific computing for the efficient design of machine learning (ML) and artificial intelligence (AI) accelerators, or high-performance parallel computation systems built to process data-intensive application workloads like neural networks. He is also focused on the optimization of system-on-chip integrated circuits for end-to-end ML and AI implementations.
His research results have been published in many top solid-state conferences and journals, including the International Solid-State Circuits Conference, the IEEE Symposium on VLSI Technology & Circuits, and the IEEE Journal of Solid-State Circuits.
Ju’s current project proposes a unified, efficient processing architecture combining AL/ML accelerator architecture and instruction-based, general-purpose computing architecture to reduce the data transfer, energy, and latency costs of traditional, heterogeneous system-on-chip.
In addition, Ju aims to improve the energy efficiency of traditional computer architecture systems using compute-in-memory techniques.
“My career goal is to become a recognized leader and innovator in the field of semiconductors,” Ju said. “I envision establishing myself as a prominent researcher, contributing significantly to the advancement of VLSI designs and computer architecture — developing impactful, cutting-edge, and practical AL/ML hardware techniques for both academia and industry.”
Ju is also mentored by his thesis committee members Russell Joseph, associate professor of electrical and computer engineering and of computer science; and Seda Ogrenci, professor of electrical and computer engineering and of computer science at Northwestern Engineering.