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ECE Seminar Series

The seminar series explores cutting-edge research in all areas of ECE, facing the grand challenges of our time. It focuses on a wide range of topics in ECE, including microelectronics, photonics and unconventional computing (both quantum and non-quantum) in the post-Moore era, and the theory and applications of machine learning and AI. The series will feature some of the most promising and established researchers in the field, and provide a unique opportunity for participants to learn about the latest developments and engage in discussions with experts. Additionally, it will promote diversity by featuring a diverse range of speakers and perspectives, ensuring the broad accessibility of the latest ideas and breakthroughs.

Upcoming ECE Distinguished Lectures at the ECE Seminar Series

More ECE Seminars Coming Soon!

Past ECE Distinguished Lectures at the ECE Seminar Series

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Urbashi Mitra, Professor of ECE at the University of Southern California

"How Designing an Application-specific Algorithm Led to a New Form of Reinforcement Learning"

Mitra's Talk – March 10 (Fri), 2023 @2:00pm | Harold Frank Hall (HFH), Rm. 1104

Urbashi Mitra received the B.S. and the M.S. degrees from the University of California at Berkeley and her Ph.D. from Princeton University. Dr. Mitra is currently the Gordon S. Marshall Professor in Engineering at the University of Southern California with appointments in Electrical & Computer Engineering and Computer Science. She was the inaugural Editor-in-Chief for the IEEE Transactions on Molecular, Biological and Multi-scale Communications. She has been a member of the IEEE Information Theory Society's Board of Governors (2002-2007, 2012-2017), the IEEE Signal Processing Society’s Technical Committee on Signal Processing for Communications and Networks (2012-2016), the IEEE Signal Processing Society’s Awards Board (2017-2018), and the Chair/Vice-Chair of the IEEE Communication Theory Technical Committee (2017-2020).  Dr. Mitra is a Fellow of the IEEE. (more...)

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John Martinis, Professor of Physics at UC, Santa Barbara

"My Trek from Fundamental to Industrial Research: Quantum Systems Engineering"

Martinis' Talk – Feb 17, 2023 (Fri) @2:00pm | Engineering Science Building (ESB), Room 1001

John Martinis did pioneering experiments in superconducting qubits in the mid 1980’s for his PhD thesis.  He has worked on a variety of low temperature device physics during his career, focusing on quantum computation since the late 1990s.  He was awarded the London Prize in Low temperature physics in 2014 for his work in this field. From 2014 to 2020 he worked at Google to build a useful quantum computer, culminating in a quantum supremacy experiment in 2019. He was awarded the John Stewart Bell prize in 2021.

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Justin Solomon, Associate Professor of EECS at Massachusetts Institute of Technology

"Volumetric Methods for Modeling, Deformation, and Correspondence"

Solomon's Talk – Feb 3 (Fri), 2023 @2:00pm  | Engineering Science Building (ESB), Room 1001

Justin Solomon is an associate professor in MIT's Department of Electrical Engineering and Computer Science.  He leads the Geometric Data Processing group in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), which studies problems at the intersection of geometry, large-scale optimization, and applications in machine learning and computer graphics.

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Dr. Masoud Mohseni, Senior Research Scientist at Google Quantum AI Laboratory

"Quantum-inspired Nonlocal Monte Carlo for Optimization and Sampling"

Mohseni's Talk – Jan 20 (Fri), 2023 @2:00pm | Engineering Science Building (ESB), Room 1001

Dr. Masoud Mohseni is a Senior Research Scientist at Google Quantum Artificial Intelligence Laboratory. He was formerly a research scientist and a principal investigator at the Research Lab of Electronics at MIT, where he was also a scientific consultant at BBN Technologies on unconventional computing. His current research addresses some of the hard problems at the interface of artificial intelligence, quantum computing, and statistical physics. He leads the development of quantum-inspired heuristic algorithms at Google. He led the development and management of the open-source software platform known as "TensorFlow Quantum," which was launched in 2020 (more...)