- Bnc-faculty-all-list - ecn.purdue.edu

Webinar by Prof. on David I. Inouye "Unifying and Advancing the Science of Deep Distribution Alignment"
by Gupta, Sumeet Kumar 25 Aug '22

25 Aug '22

Unifying and Advancing the Science of Deep Distribution Alignment Prof. David I. Inouye Purdue University Tuesday, August 30, 2022: 4 PM-5 PM Zoom link: https://purdue-edu.zoom.us/j/3164232249 Abstract Distribution alignment has the opposite objective of classification. While classification finds a representation that separates two distributions, alignment finds a representation that brings together two distributions. Alignment has been used in many recent machine learning applications including domain generalization, causal discovery, and fair representation learning. Despite these important applications, distribution alignment research lacks a unified and systematic conceptual framework and has primarily focused on GAN-based adversarial alignment for images. To address this gap, I will present a unifying alignment framework that encompasses alignment concepts, measures, algorithms, and applications. Specifically, I will formalize the definition of distribution alignment, develop novel non-adversarial alignment measures and algorithms, and discuss alignment applications in causal discovery and domain generalization. Ultimately, this work aims to advance the science of distribution alignment to enable the next generation of contextually aware and robust AI systems. Bio Prof. David I. Inouye is an assistant professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He leads the Probabilistic and Understandable Machine Learning Lab, which focuses on the fundamentals of distribution alignment, probabilistic models, and explainable AI. More recently, he is interested in distribution alignment including new alignment algorithms, measures, and applications such as causality and domain generalization. On the explainable AI side, he is interested in distribution shift explanations and tractable uncertainty quantification. Previously, he was a postdoc at Carnegie Mellon University working with Prof. Pradeep Ravikumar. He completed his Computer Science PhD at The University of Texas at Austin in 2017 advised by Prof. Inderjit Dhillon and Prof. Pradeep Ravikumar. He was awarded the NSF Graduate Research Fellowship (NSF GRFP) Host Sumeet Kumar Gupta, guptask(a)purdue.edu, 765 494 3484

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Canceled: Webinar by Prof. David Inouye (Purdue) on "Unifying and Advancing the Science of Deep Distribution Alignment"
by Gupta, Sumeet Kumar 25 Aug '22

25 Aug '22

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Webinar by Prof. David Inouye (Purdue) on "Unifying and Advancing the Science of Deep Distribution Alignment"
by Gupta, Sumeet Kumar 25 Aug '22

25 Aug '22

Unifying and Advancing the Science of Deep Distribution Alignment Prof. David I. Inouye Purdue University Tuesday, August 30, 2022: 4 PM-5 PM Zoom link: https://purdue-edu.zoom.us/j/3164232249 Abstract Distribution alignment has the opposite objective of classification. While classification finds a representation that separates two distributions, alignment finds a representation that brings together two distributions. Alignment has been used in many recent machine learning applications including domain generalization, causal discovery, and fair representation learning. Despite these important applications, distribution alignment research lacks a unified and systematic conceptual framework and has primarily focused on GAN-based adversarial alignment for images. To address this gap, I will present a unifying alignment framework that encompasses alignment concepts, measures, algorithms, and applications. Specifically, I will formalize the definition of distribution alignment, develop novel non-adversarial alignment measures and algorithms, and discuss alignment applications in causal discovery and domain generalization. Ultimately, this work aims to advance the science of distribution alignment to enable the next generation of contextually aware and robust AI systems. Bio Prof. David I. Inouye is an assistant professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He leads the Probabilistic and Understandable Machine Learning Lab, which focuses on the fundamentals of distribution alignment, probabilistic models, and explainable AI. More recently, he is interested in distribution alignment including new alignment algorithms, measures, and applications such as causality and domain generalization. On the explainable AI side, he is interested in distribution shift explanations and tractable uncertainty quantification. Previously, he was a postdoc at Carnegie Mellon University working with Prof. Pradeep Ravikumar. He completed his Computer Science PhD at The University of Texas at Austin in 2017 advised by Prof. Inderjit Dhillon and Prof. Pradeep Ravikumar. He was awarded the NSF Graduate Research Fellowship (NSF GRFP) Host Sumeet Kumar Gupta, guptask(a)purdue.edu, 765 494 3484 ________________________________________________________________________________ Microsoft Teams meeting Join on your computer or mobile app Click here to join the meeting<https://teams.microsoft.com/l/meetup-join/19%3ameeting_MjJlNjRlYmQtMTc4Ny00…> Meeting ID: 226 572 305 065 Passcode: 5zUnQM Download Teams<https://www.microsoft.com/en-us/microsoft-teams/download-app> | Join on the web<https://www.microsoft.com/microsoft-teams/join-a-meeting> Join with a video conferencing device purdue(a)m.webex.com Video Conference ID: 115 134 392 0 Alternate VTC instructions<https://www.webex.com/msteams?confid=1151343920&tenantkey=purdue&domain=m.w…> Learn More<https://aka.ms/JoinTeamsMeeting> | Meeting options<https://teams.microsoft.com/meetingOptions/?organizerId=c2039060-5561-407c-…> ________________________________________________________________________________

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Deepanshu Dutta - What’s Inside Your Phone? NAND Flash Memory: Past, Present, Future
by Bragg, Amelia Katherine 13 Jul '22

13 Jul '22

Zoom Link: https://purdue-edu.zoom.us/j/99248876187 [cid:image001.png@01D89695.8EFA4710]

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Webinar by Prof. Junjie Qin (Purdue) on "Mobile Storage for Demand Charge Reduction"
by Gupta, Sumeet Kumar 20 May '22

20 May '22

Mobile Storage for Demand Charge Reduction Prof. Junjie Qin Purdue University Tuesday, May 24, 2022: 1 PM-2 PM Zoom link: https://purdue-edu.zoom.us/j/3164232249 Abstract EV batteries, an increasingly prominent type of energy resources, are largely underutilized. In this talk, we will discuss a new business model that monetizes underutilized EV batteries to significantly reduce the demand charge portion of many commercial and industrial electricity users’ electricity bills. This business requires minimal hardware to enable discharging batteries of electric vehicles and a sharing platform that matches EVs to commercial electricity users in real time. Using real meter data, we establish the financial viability of the business by studying the temporal distribution of user requests. We then discuss user-side and platform-side challenges for implementing this business. Bio Junjie Qin is an Assistant Professor in the School of Electrical and Computer Engineering at Purdue University. Before joining Purdue, he was a postdoctoral researcher at UC Berkeley, working with Prof. Kameshwar Poolla and Prof. Pravin Varaiya. Junjie obtained a Ph.D. degree in Computational and Mathematical Engineering (2018) from Stanford University, where he also received an M.S. degree in Civil and Environmental Engineering (2011) and an M.S. degree in Statistics (2017). His research interests include electric energy systems and transportation networks. He has received the 2022 Google Research Scholar Award, the 2020 O. Hugo Schuck Best Paper Award by the American Automatic Control Council, the Best Student Paper Award at the 23rd IEEE International Conference on Intelligent Transportation Systems, the Best Student Paper Finalist at the 55th IEEE Conference on Decision and Control, and the Satre family fellowship on energy and sustainability. Host Sumeet Kumar Gupta, guptask(a)purdue.edu, 765 494 3484

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Webinar by Prof. Luis Gomez (Purdue) on "Computational Electromagnetics tools for improving and studying TMS targeting"
by Gupta, Sumeet Kumar 13 May '22

13 May '22

Computational Electromagnetics tools for improving and studying TMS targeting Prof. Luis Gomez Purdue University Tuesday, May 17, 2022: 1 PM-2 PM Zoom link: https://purdue-edu.zoom.us/j/3164232249 Abstract Transcranial magnetic stimulation (TMS) is a noninvasive technique used for neuroscience research and treatment of psychiatric and neurological disorders. During TMS, a current-carrying coil placed on the scalp induces an electric field that modulates targeted neuronal circuits. Computational simulations of the electric field (E-field) induced by TMS are increasingly used to gain a mechanistic understanding of the effect of TMS on the brain and to inform its administration. However, these computational frameworks neglect the many inherent contingencies of the TMS setup. These inherent contingencies oftentimes result in an E-field that is different from the one realized in practice. To ensure safe and effective use of computational simulation results, we are developing a new variation aware computational E-field solver that predicts the expected value of the electric field, as well as confidence intervals indicating potential variability in the actual E-field dose delivered. Our framework leverages fast-methods enabling its use for determining population level optimum coil placements for targeting the dorsolateral prefrontal cortex (DLPFC) in depression treatments. For example, the predicted optimum coil placement across individuals corroborates recent studies indicating that the clinically prescribed coil placement is suboptimal. Our framework also enables the computation of individualized optimum coil placements while considering limitations in the precision and accuracy of the TMS coil positioning protocol and possible segmentation errors. Finally, I will briefly describe other ongoing efforts in my lab including designing and fabricating focal TMS coils, and novel conductivity measurement techniques. Bio Dr. Luis Gomez, Ph.D. is an Assistant Professor of Electrical and Computer Engineering at Purdue University. Prior to Purdue, Dr. Gomez was a postdoctoral associate at the Department of Psychiatry & Behavioral Sciences at Duke University Medical School. His research interests are primarily in computational electromagnetism, with a focus on wave propagation in highly heterogenous materials, volume integration equations, electromagnetic imaging and optimization, and uncertainty quantification of brain stimulation modalities. Dr. Gomez received his Ph.D. in electrical engineering and his M.S. in electrical engineering and applied math from the University of Michigan. Host Sumeet Kumar Gupta, guptask(a)purdue.edu, 765 494 3484 ________________________________________________________________________________ Microsoft Teams meeting Join on your computer or mobile app Click here to join the meeting<https://teams.microsoft.com/l/meetup-join/19%3ameeting_YWI1OTQwNmYtNDkzOC00…> Learn More<https://aka.ms/JoinTeamsMeeting> | Meeting options<https://teams.microsoft.com/meetingOptions/?organizerId=c2039060-5561-407c-…> ________________________________________________________________________________

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Zoom Seminar by LNOI expert Mengjie Yu from USC (formerly Loncar and Lipson group)
by Bhave, Sunil A 01 May '22

01 May '22

I have invited Professor Mengjie Yu of USC to give a Zoom seminar. She did her phd with Mchal lipson and postdoc with Marko loncar and just recently started at USC. She is certainly a premier expert in LNOI photonics. https://viterbi.usc.edu/directory/faculty/Yu/Mengjie https://purdue-edu.zoom.us/j/94820666697

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Dr. Mengjie's Seminar
by Abrol, Sangeeta Saddul 29 Apr '22

29 Apr '22

Dear All - Here is an upcoming seminar by Dr Mengjie Yu from UCLA that might be of interest to you: Topic : Nonlinear Photonics Based on Thin‐Film Lithium Niobate Date : Thursday May 5th, 2022 Time : 12.00pm - 1.00pm Virtual Link: https://purdue-edu.zoom.us/j/94820666697 Thanks, Best, Sangeeta Abrol Lead Administrative Assistant to the Director | Birck Nanotechnology Center 1205 West State St | West Lafayette, IN 47907 abrols(a)purdue.edu<mailto:abrols@purdue.edu> |purdue.edu/discoverypark/birck<http://purdue.edu/discoverypark/birck> o: 765-494 3509 | BRK 1027 [cid:image001.png@01D5E1BC.DCF172D0]

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Prof. Gregory Sotzing's Seminar
by Abrol, Sangeeta Saddul 29 Apr '22

29 Apr '22

Hello All - This is a reminder of an upcoming seminar today Friday April 29th at 11.00am by Prof. Gregory A. Sotzing that might be of interest. Topic: Polymer Design for Wearable Fabric Electronics, High Power Dielectrics and Hemp Derived Thermoplastic Biomaterials Please join: In person : BRK_1001 Virtual : https://purdue-edu.zoom.us/j/96743534279 Thanks, Best, Sangeeta Abrol Lead Administrative Assistant to the Director | Birck Nanotechnology Center 1205 West State St | West Lafayette, IN 47907 abrols(a)purdue.edu<mailto:abrols@purdue.edu> |purdue.edu/discoverypark/birck<http://purdue.edu/discoverypark/birck> o: 765-494 3509 | BRK 1027 [cid:image001.png@01D5E1BC.DCF172D0]

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Photoshoot
by Abrol, Sangeeta Saddul 29 Apr '22

29 Apr '22

Dear All Members of the Faculty, We are organizing a photographer for a half day or full day photo shoot at Birck. The date is currently being finalized. We wanted to know if there is any interest of having photos taken in your lab. Similar to last time, it will focus on people in "action shots" but also equipment. Let Neil Dilley and myself know of your interest. Thanking you, Best, Sangeeta Abrol Lead Administrative Assistant to the Director | Birck Nanotechnology Center 1205 West State St | West Lafayette, IN 47907 abrols(a)purdue.edu<mailto:abrols@purdue.edu> |purdue.edu/discoverypark/birck<http://purdue.edu/discoverypark/birck> o: 765-494 3509 | BRK 1027 [cid:image001.png@01D5E1BC.DCF172D0]

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