IEEE CC EVENT – 20 July @ 6 PM
PROFESSOR Yufei Ding PRESENTS
Register for FREE Event Here
Location – Rusty’s Pizza
5934 Calle Real, Goleta, CA 93117
6:00 PM – Free Pizza, Salad Bar & Beverage
6:25 PM – Central Coast Status
6:30 PM – Professor Yufei Ding Presents
You are invited to the IEEE Central Coast Event at Rusty’s Pizza on July 20 at 6 PM, where Dr. Yufei Ding PhD. UCSB – CS/ECE, will honor us with a talk on Quantum Computing, “Full-stack System Optimization for Quantum Computing.” In this talk, she will introduce some of her recent work (and visions) in overcoming obstacles hindering practical Quantum Computing.
Guests are welcome.
Best regards, Ruth Franklin, IEEE Central Chair
Preview: The second quantum revolution, the transition from quantum theory to quantum engineering, is leading us towards practical quantum computing. However, there are still many obstacles hindering practical quantum computing. In this talk, I give my vision about the essential role of computing systems for future quantum computing development, with a focus on the methodologies for transferring the knowledge we have learned in building classical computing systems to the new context. In particular, I will introduce our recent work as an implementation of this vision, e.g., general compiler support with efficient qubit mapping, domain-specific compiler designs enabled by new intermediate representations, design flow for domain-(application) quantum accelerator designs, and automatic surface code synthesis towards future fault-tolerant quantum computing.
Professor Yufei Ding of UCSB – CS-ECE
Technical bio: Yufei Ding joined UCSB’s Department of Computer Science (with a joint appointment in the Department of Electrical & Computer Engineering) as an Assistant Professor in November 2017. She received her PhD in Computer Science from North Carolina State University, and BS and MS in Physics from University of Science and Technology of China and the College of William and Mary, respectively. Her research interests lie in the broad fields of domain-specific language design, architecture and compiler optimization, and hardware acceleration. Her current research focuses on building high-performance, energy-efficient, and high-fidelity programming frameworks for emerging technologies such as quantum computing, machine learning, and deep learning. She is a recipient of NSF CAREER Award (2020), IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing (2019), NCSU Computer Science Outstanding Dissertation Award (2018), NCSU Computer Science Outstanding Research Award (2016), and Distinguished Paper Award at OOPLSA (2020).