SUNMONTUEWEDTHUFRISAT
Events for the 2nd week of September
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Professional Enhancement Seminar
Tue, Sep 08, 2020 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milan L. Mashanovitch, CEO of Freedom Photonics LLC
Talk Title: Starting Your Own Technology Company - A Photonics Perspective
Abstract: In this presentation, followed by a Q&A session, we will discuss what is needed when starting up your own technology company in the United States. The presentation will review the startup ecosystem, societal economics, government support, small business programs, funding models, exit strategies, and more, through examples from the field of photonics.
Biography: Dr. Milan Mashanovitch is the Chief Executive Officer of Freedom Photonics, a photonics company based in Santa Barbara, California.
Dr. Mashanovitch co-founded Freedom Photonics in 2005, and has served as Director of Business Development from 2005-2010, General Manager from 2010-2016, and as CEO since 2016. In these different roles, he has helped grow the company to become a leader in innovative photonic components, with >50 employees, and >10 products, manufactured in Santa Barbara.
Dr. Mashanovitch has 20 years of experience working in the field of photonics, spanning over design, fabrication, testing and packaging of photonic integrated circuits, combined with 10 years of management and business development experience.
Prior to Freedom Photonics, Dr. Mashanovitch has worked at the University of California Santa Barbara as a Scientist, on photonic integrated circuits in Indium Phosphide, as well as an Adjunct Professor teaching graduate level classes on semiconductor lasers and photonic ICs.
Dr. Mashanovitch has co-authored 160 papers, many invited, on photonic integrated circuits, semiconductor lasers and various photonic devices. He holds 9 patents, and has co-authored the second edition of the "Diode Lasers and Photonic Integrated Circuits" textbook. He is very active in the photonics technical community, participating on technical committees of many conferences. He is a Senior Member of IEEE, and currently serves on the Board of Governors for the IEEE Photonics Society.
Dr. Mashanovitch holds a Degree in Electrical Engineering from the University of Belgrade in Serbia, and M.S. and Ph.D. degrees from the University of California in Santa Barbara.
Host: Mihailo Jovanovic
More Info: https://usc.zoom.us/j/95238378289?pwd=ZU1Ga2xqRk16anlmOENKU2ZjWmNLQT09
More Information: b73465f7-1382-4657-b48d-8f573e9d4c88.png
Audiences: Everyone Is Invited
Contact: Cathy Huang
Event Link: https://usc.zoom.us/j/95238378289?pwd=ZU1Ga2xqRk16anlmOENKU2ZjWmNLQT09
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Sep 09, 2020 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alan Mishchenko, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
Talk Title: Circuit-Based Intrinsic Methods to Detect Overfitting
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The focus of this talk is on intrinsic methods to detect overfitting. By intrinsic methods, we mean methods that rely only on the model and the training data, as opposed to traditional methods that rely on performance on a test set or on bounds from model complexity. We propose a family of intrinsic methods, called Counterfactual Simulation (CFS), which analyze the flow of training examples through the model by identifying and perturbing rare patterns. By applying CFS to logic circuits we get a method that has no hyper-parameters and works uniformly across different types of models such as neural networks, random forests and lookup tables. Experimentally, CFS can separate models with different levels of overfit using only their logic circuit representations without any access to the high level structure. By comparing lookup tables, neural networks, and random forests using CFS, we get insight into why neural networks generalize. The paper appeared at ICML 2020: https://people.eecs.berkeley.edu/~alanmi/publications/2020/icml20_cfs.pdf
Biography: Alan graduated with M.S. from Moscow Institute of Physics and Technology (Moscow, Russia) in 1993 and received his Ph.D. from Glushkov Institute of Cybernetics (Kiev, Ukraine) in 1997. In 2002, Alan joined the EECS Department at the University of California, Berkeley, where he is currently a full researcher. His research is in computationally efficient logic synthesis and formal verification.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQ
Audiences: Everyone Is Invited
Contact: Talyia White