Association of Chinese Scholars in Computing

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[ACSIC Speaker Series #21]

AUGUST 28, 2020, 2:00 PM EDT

My experience with quantum computing research

Yufei Ding, University of California at Santa Barbara

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ABSTRACT: Quantum computing (QC) has become the new "race to the moon" pursued with national pride and tremendous investments, spurring interest and motivation across academia and industry. Big companies like Google, Microsoft, IBM have initialized or deepened their efforts on QC. Los Alamos National Laboratory, NASA's Ames Research Center, and many other national labs are installing the latest quantum devices. Funding agencies like NSF and DoE have announced specialized programs for quantum computing.

In this talk, I will share my experience with quantum computing research. I will give some background about quantum computing and introduce my group’s recent work on building a consolidated quantum compiler for addressing the optimization and debugging challenges in the current era of Noisy Intermediate-Scale Quantum Computing.

I will also talk about how I adapted to the new field of quantum computing since I started my faculty career at UCSB three years ago, and tackled the unique challenges, like how to efficiently grasp the knowledge to understand quantum papers, how to find topics that could leverage my previous expertise in non-quantum fields, what is my experience of starting a new direction as an assistant professor, as well as my funding experience with quantum computing topics.

BIO: Yufei Ding joined the Department of Computer Science (with a joint appointment in the Department of Electrical & Computer Engineering), University of California at Santa Barbara as an Assistant Professor in Nov 2017. She received her Ph.D. in Computer Science from North Carolina State University and B.S. and M.S. 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 received the NCSU Computer Science Outstanding Research Award in 2016 and Computer Science Outstanding Dissertation Award in 2018. She is also a recipient of the 2019 IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High-Performance Computing.