Lecture Series Archive

How a Scottish academic in 1873 set the stage for today’s global communications

Rob Rowlands

Mr. Rob Rowlands
Volunteer Faculty
Engineering Department, SSU

Thu, 03/02/2023

Abstract: Hard as it is to believe today, the connection between electricity and magnetism was not made until early in the 19th Century. James Clerk Maxwell brought together field theories from Gauss, Ampere and Faraday into a unified set of equations. At the publication of his “Treatise on Electricity and Magnetism” 1873, radio had not yet been demonstrated and the electromagnetic properties of light were not understood. Today these equations are the basis of our modern world allowing us to carry powerful communications tools in our pocket or place a telescope in space a million miles away. The talk is a review of some of the miracles that followed from the math, though understanding the vector math is not required (119 words).

Bio: Rob received a Bachelor of Engineering degree in electrical engineering from the University of Canterbury in Christchurch, New Zealand in 1971. He was a Transmission Engineer in the NZ Post Office for 22 years, followed by 21 years with HP and Agilent in the SF Bay Area in Business Development and sales of communications test equipment. Since 2017 he has been a volunteer lecturer teaching a popular RF Test Laboratory class at Sonoma State University. He is semi-retired but still selling test equipment for Gap Wireless. Rob is a life member of IEEE

Snap-Shot 3D Cameras

Weijian Yang

Dr. Weijian Yang
Associate Professor
Department of Electrical and Computer Engineering, University of California, Davis

Thu, 02/16/2023

Abstract: Three-dimensional (3D) imaging through a compact device could enable many applications in mobile consumer electronics and biomedical endoscopy. Conventional 3D cameras are bulky and require taking multiple photos to synthesize a 3D scene. Here, I will introduce a new type of 3D camera. It replaces all the bulk optics by a single layer of optical mask and can be made very compact. It takes a snap-shot of the 3D object or scene, and then recovers the 3D information through computational algorithms. Here, I will discuss the two 3D cameras that we recently developed, which can image 3D microscopic objects or 3D macroscopic scenes. Both cameras are composed of a single piece of randomly positioned microlens array and an image sensor. We develop highly-efficient computational algorithms to reconstruct the 3D objects and 3D scenes from a single camera exposure. Our 3D cameras open new avenues for high speed 3D imaging with a compact device footprint.

Bio: Weijian Yang is an associate professor at the Department of Electrical and Computer Engineering at the University of California, Davis. He received his undergraduate degree from Peking University and a PhD from the University of California, Berkeley, all in Electrical Engineering. After postdoctoral training in neuroscience at Columbia University, Dr. Yang started his own laboratory at UC Davis in late 2017. His current research aims to develop advanced optical methods and neurotechnologies to interrogate and modulate brain activity, with a goal to understand how neural circuits organize and function and how behaviors emerge from neuronal activity. He is a recipient of the Career Awards at the Scientific Interface from Burroughs Wellcome Fund in 2016, the Early Career Award from National Science Foundation in 2019, and the Science and PINS Prize for Neuromodulation (second prize) from American Association for the Advancement of Science in 2021.

Introduction to Microgrids

Bob Salter

Mr. Bob Salter
Energy Systems Consultant

Thu, 02/02/2023

Abstract: Most consumers receive their electricity via electrical grids consisting of utility generation plants and transmission and distribution networks. In most highly developed and populated parts of the world, consumers receive their electricity continuously and reliably most of the time. Unfortunately, disruptions do occur for various reasons, and with significantly negative social, economic, and public safety impacts. In addition, modern utility rate structures can significantly impact electricity costs to consumers due to surcharges based on tiered and time-of-use pricing and peak demand charges. In lesser populated and/or more remote locations, electrical grids do not exist at all, and localized solutions are required.

This lecture will discuss Microgrids as a solution to some of the challenges we face; we will explore definition of microgrid; types of microgrids; main elements of microgrids including DERs and DERMS; and review use case and value proposition examples. We will also explore steps required to design a microgrid and some of the simulation and modeling tools used.

Bio: Bob Salter has 47 years of industry experience in Energy and Mechanical Systems Engineering, Marketing, Construction, Commissioning, Compliance and Field Services. From 2008 Bob has focused on design and execution of major projects involving electrical power distribution, monitoring, controls and protection. Bob is a Registered Professional Engineer (State of California, Electrical) since 1973; received his BS-EE from Worcester Polytechnic Institute in 1976, and his MBA (with concentration in Finance) from San Francisco State University in Finance in 1982. Bob is a Life Senior Member in IEEE, current Treasurer of OEB Section, and past Officer at various Chapter, Section and Council Levels. Bob is currently a volunteer Professor on the SSU Engineering Department faculty.

Infrared Oscilloscopes: Sampling 30-THz Waveforms for Next-Generation Spectroscopy

William Putnam

Dr. William Putnam
Assistant Professor
ECE Department, UC Davis, Davis, CA

Thu, 11/17/2022

Abstract: In electronic devices like field-effect transistors, applied electric fields, up to hundreds of gigahertz in frequency, control electron motion. Recently, it has been demonstrated that the electric fields of ultra-intense laser pulses, i.e. electric fields in the tera- to petahertz (THz to PHz) regime, can similarly control electric currents around gas-phase atoms. In this talk, I will describe recent efforts to extend these early demonstrations of THz- and PHz-speed electronics from gaseous media to solid-state, microelectronic devices. Specifically, I will describe nanoantenna-based devices in which electric currents can be switched on and off by individual oscillations of the electric field of an infrared laser pulse. I will show that these devices can be used to sample >30-THz electric field waveforms in the time domain, and I will overview one of the exciting potential applications of these devices: field-resolved infrared spectroscopy.

Bio: William Putnam received his Ph.D. in EECS from MIT as well as undergraduate degrees in EECS and physics. Following his Ph.D. he held postdoctoral positions at MIT and the Center for Free-Electron Laser Science (CFEL) at the University of Hamburg, Germany. After his postdoctoral work and prior to joining the faculty at UC Davis, William spent several years as a staff scientist at Northrop Grumman’s basic research laboratory, NG Next where he worked on ultrafast electronics and frequency comb technology. From his undergraduate years to his postdoctoral work to his time in industry, William’s research has centered around both fundamental and applied studies of optics and quantum electronics.

Learning Preferences for Interactive Autonomy

Erdem Bıyık

Dr. Erdem Bıyık
Postdoctoral Researcher
Center for Human-Compatible Artificial Intelligence, UC, Berkeley, CA

Thu, 11/03/2022

Abstract: In human-robot interaction or more generally multi-agent systems, we often have decentralized agents that need to perform a task together. In such settings, it is crucial to have the ability to anticipate the actions of other agents. Without this ability, the agents are often doomed to perform very poorly. Humans are usually good at this, and it is mostly because we can have good estimates of what other agents are trying to do. We want to give such an ability to robots through reward learning and partner modeling. In this talk, I am going to talk about active learning approaches to this problem and how we can leverage preference data to learn objectives. I am going to show how preferences can help reward learning in the settings where demonstration data may fail, and how partner-modeling enables decentralized agents to cooperate efficiently.

Bio: Dr. Erdem Bıyık is a postdoctoral researcher at the Center for Human-Compatible Artificial Intelligence at University of California, Berkeley. He has received his B.Sc. degree from Bilkent University, Turkey, in 2017; and Ph.D. degree from Stanford University in 2022. His research interests lie in the intersection of robotics, artificial intelligence, machine learning and game theory. He is interested in enabling robots to actively learn from various forms of human feedback and designing robot policies to improve the efficiency of multi-agent systems both in cooperative and competitive settings. He also worked at Google as a research intern in 2021 where he adapted his active robot learning algorithms to recommender systems. He will join the University of Southern California as an assistant professor in 2023.