MSE 598-DM Spring 2021

Course director

Lucas K. Wagner

Assistant professor of physics

I have an office, but I don’t go to it and you shouldn’t either. Maybe in future semesters!

Online links

Summary of the course

This course is a multidisciplinary introduction to topics at the intersection of materials and data science. Corresponding to this, it brings in speakers and activities from 6 different departments (computer science, information science, statistics, physics, materials science, and mechanical engineering) to provide their own perspectives on this subject.


Expectations: hands-on learning

Each unit, noted below in the schedule, will involve hands-on sessions. You will turn in a PDF report on each of your hands on activities. The report should include a narrative about what you are doing and why. Learning how to do this is an important part of doing science.


Weeks 1-5 focus on tools that will be used in the remaining weeks. Weeks 6-15 will be hands-on applications, each led by a different faculty member.

Week Tuesday Thursday Topic Instructor
1 1/26 1/28 Introduction, python basics Lucas Wagner
2 2/2 2/4 Python for data science day1 and day2 Luke Olson
3 2/9 2/11 Visualization Hands-on activity Matthew Turk
4 2/16 2/18 Generalized linear models (1), Bayesian models (2) Bo Li
5 2/23 2/25 Intro to material science for non-experts Day 2 Lucas Wagner
6 3/2 3/4 Band alignment Day 2 Andre Schleife
7 3/9 3/11 Defect ID using statistical learning methods Notes Harley Johnson
8 3/16 3/18 Image processing for TEM Pinshane Huang
9 3/23 3/25 4CeeD, Bracelet, Senselet Klara Nahrstedt
10 3/30 4/1 4CeeD, Bracelet, Senselet Klara Nahrstedt
11 4/6 4/8 Uncertainty quantification Slides / Exercise Dallas Trinkle
12 4/13 4/15 BREAK, Computing resources Lucas Wagner
13 4/20 4/22 Graphene ResQ Elif Ertekin
14 4/27 4/29 Graphene ResQ Elif Ertekin
15 5/4 TBA