Each quarter, the UC Davis College of Engineering hosts an outstanding researcher to deliver a distinguished lecture that is open to all students, faculty, staff and the public. These lectures are an excellent opportunity for our College to bring academic and industry experts to UC Davis to interact and exchange ideas with faculty and students. This year, we have two prominent individuals slated to discuss a variety of topics for the 2019-20 Distinguished Lecture Series.
Winter 2020 Distinguished Lecture
“Breaking Rules for Cost-Effective Storage of Energy”
Lynden A. Archer
Thursday, January 23, 2020 4:00 pm – Student Community Center MPR
Archer is the James A. Friend Family Distinguished Professor of Chemical and Biomolecular Engineering and David Croll Director of the Cornell Energy Systems Institute. His research focuses on transport properties of polymers and polymer-nanoparticle hybrid materials and their applications for electrochemical energy storage. Archer received his Ph.D. in chemical engineering from Stanford University in 1993 and was a postdoctoral scholar at AT&T Bell Laboratories in 1994. He is a member of the National Academy of Engineering and fellow of the American Physical Society.
Archer will discuss how rechargeable electrochemical cells based on earth-abundant metallic anodes, including sodium, zinc and aluminum, offer the potential for transformative advances in cost-effective storage of electrical energy. Such cells are under active development worldwide because they provide a path towards battery systems capable of meeting the performance and cost requirements for dispatchable electric power generation from renewable, but intermittent sources. Archer will outline the stability limits for metal electrodeposition processes in liquid and semisolid structured electrolytes and, on that basis, proposes electrode and anode/electrolyte interphase design principles for enabling stable electrodeposition of metals.
Spring 2020 Distinguished Lectures
Blockchain: An Overview”
Dr. Sandra K. Johnson
Friday, April 10, 2020 4:00 pm – Jan Shrem and Maria Manetti Shrem Museum of Art
Johnson is the founder, CEO and CTO for Global Mobile Finance, Inc., a fintech startup company, and the founder and CEO of SKJ Visioneering, LLC, a technology consulting company. She earned her B.S., M.S. and Ph.D. degrees, all in electrical engineering, from Southern University, Stanford University, and Rice University, respectively, becoming one of the first African-American women to earn a Ph.D. in this field.
Johnson will present an overview of blockchain, a distributed ledger technology, and discuss her experience as a “hidden figure” in engineering. Her lecture includes the specifics of blockchain as the foundation for cryptocurrencies, the emergence of blockchain as a solution for the reconciliation of peer-to-peer transactions and other interactions between non-trusted parties, distributed consensus and other blockchain concepts. She will also touch on blockchain implementations, including those for Bitcoin, Ether and implemented cryptographic algorithms. Johnson will also discuss smart contracts, safety and security and the game-changing potential of blockchain as a new methodology for disintermediating businesses.
“Safe Machine Learning”
Monday, April 27, 2020 11:00am – Student Community Center MPR
Goldwasser is the Director of the Simons Institute for the Theory of Computing and a professor of computer science at UC Berkeley. She is also the RSA Professor of Electrical Engineering and Computer Science at MIT, and a professor of computer science and applied mathematics at the Weizmann Institute of Science in Israel. Goldwasser received a B.S. in applied mathematics from Carnegie Mellon University in 1979, and M.S. and Ph.D. in computer science from UC Berkeley in 1984. Among many accolades, Goldwasser was the recipient of the ACM Turing Award for 2012. She is a member of the AAAS, ACM, NAE, NAS, Israeli Academy of Science, London Mathematical Society and Russian Academy of Science.
Goldwasser will discuss how cryptography and computational learning have shared a curious history: a scientific success for one has often provided an example of an impossible task for the other. Today, the goals of the two fields are aligned. Cryptographic models and tools can and should play a role in ensuring the safe use of machine learning. Goldwasser will present this development with its challenges and opportunities.