Exploring New Frontiers: Machine Learning Meets Materials Science seminar series

We are thrilled to announce the next installment in the Machine Learning Meets Materials Science seminar series, led by WISE researcher Maryna Pankratova from Uppsala University. This interesting initiative, part of a WISE-WASP collaboration, fosters interdisciplinary dialogue and synergy between the cutting-edge fields of materials science and machine learning.

Each seminar in the series provides a unique platform for experts from both domains to share insights and explore innovative ideas. However, the upcoming fourth seminar will feature a solo presentation by Leon Bochman, a research engineer at Chalmers E-common. Leon will deliver an introductory session on artificial intelligence and machine learning, followed by an engaging discussion of a relevant research article.

Don’t miss this opportunity to gain fresh perspectives, learn foundational AI concepts, and connect with leading minds in materials science and machine learning. Join us as we explore how these dynamic fields intersect to shape the future of science and technology!

Seminar Title: A Taste of AI in Materials Science
Date: December 5th, 2024
Time: 10:00 AM – 11:30 AM (CET)
Location: Online via Zoom https://uu-se.zoom.us/j/61866254849

Meeting ID: 618 6625 4849

Agenda

10:00 – General Introduction to AI/ML (45 minutes + Q&A)
Leon Bochman will provide a foundational overview of artificial intelligence and machine learning, exploring key concepts such as models, training paradigms, and model evaluation strategies. This session is perfect for those new to AI and curious about its applications.

10:55 – Short Break

11:10 – Paper Discussion (20 minutes)
Dive deeper into the practical applications of machine learning in materials science through an engaging discussion of a recent research paper.

Abstract:

It seems that these days AI is everywhere. But what exactly is AI? Can we use it in Materials Science? And how would we do that? In this talk I will provide a generic introduction into AI and Machine Learning, where we will discuss models, training paradigms, model evaluation strategies, and more. In the second half, I will discuss a recent paper in Materials Science that uses Machine Learning. This talk is aimed at those who have never done anything with AI, but would like to know more. The goal is to take the magic away and show you how it could be another tool in your research toolbox.

For more information on Maryna Pankratova’s research in WISE visit:

Explainable machine learning for magnetic interactions extraction