CS Colloquium: Murphy Niu (Google Quantum AI Team)
Speaker: Murphy Niu
Date: May 31st, 2023
Time: 3:30 pm
Location: HFH 1132
Host: Yufei Ding
Title: Power of Machine Learning and Optimization in Quantum Computer Design
Abstract: Towards developing a large-scale quantum computer, design automation, and associated optimization become increasingly critical. In this talk, I will review three areas of quantum computer design and operation where machine learning and advanced optimization can help improve the accuracy and performance magnitudes beyond the best existing human experts. The three areas are quantum architecture design, quantum control optimization and quantum metrology, and quantum circuit optimization. I will conclude by outlining some open areas where design automation and machine learning can become critical in pushing beyond existing technological barriers toward scalable quantum computer design.
Bio: Niu is currently a senior research scientist in the Google Quantum AI team, where her work focuses on intelligent quantum control optimization and metrology, quantum machine learning, quantum algorithm design and near-term quantum error correction. Niu applies cutting-edge deep reinforcement learning and generative models to quantum control, quantum circuit compilation, and quantum system learning using some of the largest quantum computers based on superconducting qubits.
Niu received her doctorate in theoretical and mathematical physics from MIT in 2018. She received the Claude E. Shannon Research Assistantship for her work at the intersection of photonic quantum computation, quantum error correction and quantum cryptography. Murphy Yuezhen Niu will join the Joint Center for Quantum Information and Computer Science (QuICS) in August 2023 as an assistant professor of computer science and QuICS Fellow. She will also have an appointment in the University of Maryland Institute for Advanced Computer Studies.