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May 2022

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CBEE Seminar on machine learning + materials with Taylor Sparks 5/2 at 4 PM Johnson 102
by Tadepalli, Prasad 02 May '22

02 May '22

Hello all, Some of you might find this CBEE seminar interesting (May 2, 4 pm). Please attend if you can. Prasad Tadepalli ________________________________ From: Mills, Tina K <tina.mills(a)oregonstate.edu<mailto:tina.mills@oregonstate.edu>> Sent: Thursday, April 28, 2022 9:40 AM To: CBEE All Faculty and Staff <cbee-all(a)oregonstate.edu<mailto:cbee-all@oregonstate.edu>>; CBEE Postdocs <cbee-postdocs(a)oregonstate.edu<mailto:cbee-postdocs@oregonstate.edu>>; cbee-grads(a)engr.orst.edu<mailto:cbee-grads@engr.orst.edu> <cbee-grads(a)engr.orst.edu<mailto:cbee-grads@engr.orst.edu>>; Engineering, All Faculty <all-faculty(a)engr.orst.edu<mailto:all-faculty@engr.orst.edu>> Subject: REMINDER: CBEE Seminar with Taylor Sparks Dear CBEE Graduate Students, Faculty, and Postdocs, A CBEE seminar is scheduled for Monday, May 2. Taylor Sparks, Associate Professor of Materials Science and Engineering at University of Utah will join us at 4 p.m. to deliver his talk, titled "Materials Informatics: Moving Beyond Screening Via Generative Learning Machine Learning Models." An abstract and brief speaker bio is provided below. Please try to attend if you are able. Spring Term Seminars are in-person in Johnson 102, but can also be accessed through the Zoom link provided below. Monday, May 2 4-4:50 p.m. Johnson 102 Zoom ID: 938 0547 9867 <https://oregonstate.zoom.us/j/93805479867?pwd=SkNkZElEVGx3Y0VWbUdLL2ZEcmZXd…> Passcode: cstr Materials informatics: Moving beyond screening via generative machine learning models ABSTRACT Technology progresses only as fast as the development of new, advanced materials. Materials discovery has never been more important, but it is far too slow and expensive. Materials informatics has accelerated materials development, but primarily allows us to screen known materials as opposed to truly discover new materials. Here, I will describe our efforts to generate new periodic crystalline materials by predicting crystallographic information file data using generative adversarial networks in conjunction with the newly published DiSCoVeR algorithm that combines a chemical distance metric, density-aware dimensionality reduction, clustering, and a regression model. ABOUT THE PRESENTER Dr. Sparks is an Associate Professor of Materials Science and Engineering at the University of Utah. He holds a BS in MSE from the UofU, MS in Materials from UCSB, and PhD in Applied Physics from Harvard University. He was a recipient of the NSF CAREER Award and a speaker for TEDxSaltLakeCity. When he's not in the lab you can find him running his podcast "Materialism" or canyoneering with his 4 kids in southern Utah. Tina Mills Assistant to CBEE School Head Chemical, Biological and Environmental Engineering GO BEAVS!

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