[Bnc-faculty-all-list] FW: nanoHUB Hands-on Machine Learning Workshop

[Black, Nancy Lee]

nanoHUB is excited to announce that a new workshop has been scheduled in the Fall 2021 session of our Hands-on Data Science and Machine Learning Training Series.

Series information: Our series is aimed at active researchers and educators and designed to introduce practical skills with online, hands-on activities that participants will be able to incorporate in their own work. Hands-on activities will use nanoHUB cloud computing resources, negating the need to download or install any software. All that is required of the audience is an internet connection and an hour to spare for the demonstration. After the training sessions, you will be able to continue using nanoHUB for research or education.

Recordings and associated materials from prior workshops can be found at the workshop webpage: https://nanohub.org/groups/ml/handsontraining<https://click.mail.nanohub.org/?qs=fa5d19fdba110be3328ac7c0e6aa1c23ed02fcba3677ed0156b8cb3c81979933cbdb68e347e60b1f0c742b032dda0b2b6801b71140bc86b33aa0ebe512e85b1d>

Register soon as seats are limited.

Date/Time: Wednesday, November 17, 2021 / 1:00 PM - 2:00 PM EST
Title: Integrating Machine Learning with a Genetic Algorithm for Materials Exploration
Presenter: Joe D. Kern, Georgia Institute of Technology, Ramprasad Group

Register for this workshop here<https://click.mail.nanohub.org/?qs=fa5d19fdba110be31df082c3e47a7f7022739f4c0c0d7e1a4c5fbc845fddb32d0043e5d90d2aac11e1e7121eba99c6f6e9386249d725206fe3a96af954f6a60a>

Abstract: The genetic algorithm is a computer algorithm inspired by nature: selecting parents of a generation via some fitness function, crossing-over the parent genes (reproduction), and randomly mutating the genes of the children. In this talk, we will explore how this algorithm can be used for materials discovery by:
1. Generating swift material property prediction using machine learning (ML)
2. Creating an algorithm to design new materials from combinations of prior ones
3. Integrating the ML property predictors with the design algorithm to discover new materials PolyGA, an implementation of the genetic algorithm for the polymer domain, will be used as the basis for this exploration.

Bio: Joe D Kern is a Materials Science and Engineering graduate student at the Georgia Institute of Technology in the Ramprasad Group. Prior to graduate school, he dual majored in Materials Science and Computer Science at the University of Wisconsin - Madison and spent six years in the Minnesota National Guard as an Arabic Linguist. His research involves utilizing computational techniques, such as genetic algorithms and machine learning, to expedite materials discovery in the polymer chemical space.



Regards,

Alejandro Strachan
Deputy Director, nanoHUB


Arun Mannodi Kanakkithodi (he/him/his)
Assistant Professor, School of Materials Engineering, Purdue University
https://www.mannodigroup.com/
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