Our Bureau
Tempe, AZ
Vidya Chhabria has been named a recipient of the inaugural Google ML and Systems Junior Faculty Award, which recognizes early-career faculty whose research is advancing the frontiers of machine learning and systems.
An assistant professor of electrical engineering in the School of Electrical, Computer and Energy Engineering, part of the Ira A. Fulton Schools of Engineering at Arizona State University (ASU), Chhabria’s research interests lie in computer-aided design, or CAD, for very large-scale integration, or VLSI, systems. Her work primarily focuses on physical design, optimization and analysis algorithms.
She is one of more than 50 assistant professors across 27 U.S. universities selected for the award by a distinguished group of Google engineers and researchers.
Chhabria highlights Google’s commitment to collaborating with academia and its recognition of research in leveraging machine learning for hardware design.
“Being recognized by Google via this junior faculty award is extremely rewarding, not just to me but to our entire group,” Chhabria says. “The research our group does focuses on developing electronic design automation tools, specialized software that aid in the design of computer chips behind everything from smartphones to data centers.”
Her research group develops electronic design automation tools, which are specialized software that aid in the design of computer chips used in everything from smartphones to data centers.
“Designing chips is complex, time-consuming and resource-intensive, and AI has shown enormous potential in addressing challenges of scale, automation and optimization in this area,” she says.
In addition to the award recognition, Chhabria will receive $100,000 in unrestricted funding.
She underscores the importance of this resource in supporting research projects and enabling them to move faster and increase scale when using AI to automate the design of computer chips.
“Training AI for chip design is especially challenging because of the lack of open-source, industrial-scale chip designs make it difficult to create and test AI models,” she says. “This award helps bridge that gap by creating collaboration opportunities with Google. Mentorship and access to industry perspectives — and possibly computational resources — help keep our work industry relevant and advance AI in chip design.”
Stephen Phillips, professor of electrical engineering and director of the School of Electrical, Computer and Energy Engineering, notes that awards like this have an impact that extends to students as well.
“Our students have an amazing opportunity learning from faculty like Dr. Chhabria, whose research is not only impactful but also receives recognition from industry leaders like Google,” Phillips says. “It’s incredibly motivating for students to be guided by someone shaping the future of the field.”
