DSECOP July 2026 Workshop

AAPT Summer Meeting 2026

Saturday, July 18, 2026 (afternoon) — 4 hours

A hands-on workshop on integrating data science and AI into undergraduate physics courses. Participants will work through DSECOP modules using cloud-based tools such as Google Colab, explore interactive exercises, and experience an AI-paired programming session demonstrating how large language models and data-driven methods can be meaningfully embedded in physics instruction.

DSECOP June 2023 Workshop

The Data Science Education Community of Practice (DSECOP) had its second workshop in June 26–28, 2023, at the University of Maryland, College Park.

DSECOP Participants

Slides

Below are the slides made available by the speakers of our second workshop on incorporating data science in physics curriculum listed in the order of the schedule.

Day 1, June 26

Mohammad Soltaniehha (Boston University): Overview of Fellows’ Activity
Julie Butler (University of Mount Union): Introduction to Data Science Libraries: Using Pandas, Seaborn, and Matplotlib to Analyze and Display Physics Data
Maissam Barkeshli (University of Maryland): Machine learning for physicists
Ashley Dale (Indiana University): Connecting Monte Carlo Methods to Modern AI/ML
Karan Shah (Center for Advanced Systems Understanding): Introduction to Computer Vision algorithms with applications in lab courses
Jacob Hale (DePauw University): DSECOP Module Implementation: A Guinea Pig Speaks

Day 2, June 27

Mohammad Soltaniehha (Boston University): Discussion: Tools
Anıl Zenginoğlu (University of Maryland): Learning AI from AI
Chris Orban (Ohio State University): Data Science in Introductory Physics and Physical Science: Ideas from the STEMcoding Project
Johnny Lin (University of Washington Bothell) Beginning at the Beginning: Teaching Novice Physicists Data Science Programming
Ivo Dinov (University of Michigan): Data Science Modules Enhancing the Biophysics Curriculum
Trevor David Rhone (Rensselaer Polytechnic Institute): Machine Learning in Materials Physics Education

Day 3, June 28

Anıl Zenginoğlu (University of Maryland): VSCode Setup

Announcement

The Data Science Education Community of Practice (DSECOP) is thrilled to announce its second workshop, which will be held from June 26–28, 2023, at the University of Maryland, College Park.

Goal

This year, we aim to build on the success of our first workshop. Our primary focus is to continue developing a vibrant community of educators committed to incorporating data science into the undergraduate physics curriculum.

To achieve this goal, we plan to have thought-provoking lectures and presentations from faculty members who are already engaged in this process. We will also be showcasing the latest contributions from fellows in our program who are developing innovative modules for inclusion in the existing curriculum. Additionally, we are excited to welcome participation from industry professionals who can bring their unique perspectives.

Topics

We anticipate this to be a highly interactive workshop, with plenty of time for discussion and contributed talks from all participants. Here is the schedule of the workshop. Some of the topics we plan to cover in this workshop include:

Strategies for integrating data science concepts into the undergraduate physics curriculum
Best practices for teaching data science to students with varying levels of experience
Exploring the latest tools and technologies for data analysis in the physics classroom
Sharing successful case studies of data-driven physics instruction

Apply

We encourage all physics faculty teaching undergraduate physics to apply for this workshop. We also welcome graduate students, postdocs, industry professionals, and data science enthusiasts to apply. As with our first workshop, we expect in-person attendance as this event is highly interactive.

This workshop is now closed.

DSECOP June 2022 Workshop

Thanks to all participants who attended the first DSECOP workshop! Here’s a group photo taken on the second day.

DSECOP Participants

Slides

Below are the slides from our first workshop on incorporating data science in physics curriculum listed in the order of the schedule.

Day 1, June 22

William Ratcliff (NIST & UMD): Opening Remarks
Mohammad Soltaniehha (Boston University): Overview of Fellows’ Activity
Julie Butler (DSECOP Fellow, Michigan State University): Using Neural Networks to Solve Differential Equations in Classical Mechanics
Radha Mastandrea (DSECOP Fellow, University of California Berkeley, Lawrence Berkeley National Laboratory): Introduction to Data Processing
Aaron Gilad Kusne (NIST): Teaching Machine Learning
Sebastian Atalla (DSECOP Fellow, University of North Carolina at Chapel Hill): Frequency Decomposition of NMR Spectra
Cunwei Fan (DSECOP Fellow, University of Illinois at Urbana Champaign): Spectral Clustering Method with Physics
Karan Shah (DSECOP Fellow, Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf): Learning the Schrödinger Equation
Fatemeh Bagheri (DSECOP Fellow, University of Texas Arlington): Introduction to Deep Learning
Alexis Knaub (American Association of Physics Teachers): Challenges and Pedagogy/Curriculum

Day 2, June 23

Marilena Longobardi (University of Basel): European landscape on Data Science
William Ratcliff (NIST, University of Maryland): Roundtable: Data Science Tools
Sanha Cheong (Stanford University): Developing & Teaching Statistics Course for Physics Students
Robert Craig (University of Virginia): Introduction to Python for Scientist and Engineers
Ivo Dinov (University of Michigan): Integration of Data Science into the STEM Curricula
Karen Leighly (The University of Oklahoma): Portfolio of Data Analytics Classes at University of Oklahoma
Mark Neubauer (University of Illinois at Urbana-Champaign): Data Analysis and Machine Learning Education in the Physics Department at the University of Illinois
Deborah Roudebush (QuarkNet): A Research Based Approach for Infusing 21st Century Physics into the High School Classroom
Mohammad Soltaniehha (Boston University): Discussion: Preparation/Prerequisites

Day 3, June 24

Unconference:

Incorporating Stats/DS in Physics/STEM curricula(Dinov and Cheong)
Integrating Data Science into Physics Laboratories(Letchworth-Weaver and Rivera)

Additional links and resources

Case Study: Predicting Galaxy Spins (from Ivo Dinov)

Announcement

We are delighted to announce the first workshop by the Data Science Education Community of Practice (DSECOP) to be held on June 22–24, 2022, at the Institute for Physical Science and Technology in College Park, MD.

The primary goal of this workshop is to develop a community of practice around incorporating data science into the undergraduate physics curriculum. This workshop will include lectures from faculty who are already engaged in this process and presentations from fellows in our program developing modules for inclusion in the existing curriculum. We also expect participation from the industry. There will be plenty of time for discussion and contributed talks.

This workshop is now closed.

Primary lodging will be at the dorms at the University of Maryland, conveniently located to the lectures. Lodging and meals will be $390 for the workshop.

We are looking forward to your participation in a mutually stimulating and productive DSECOP workshop!

Confirmed Speakers:

Mohammad Soltaniehha (Boston University)
Aaron Gilad Kusne (NIST)
Linda Hung (Toyota Research Institute)
Sebastian Atalla (DSECOP Fellow, University of North Carolina at Chapel Hill)
Fatemeh Bagheri (DSECOP Fellow, University of Texas Arlington)
Julie Butler (DSECOP Fellow, Michigan State University)
Radha Mastandrea (DSECOP Fellow, University of California Berkeley, Lawrence Berkeley National Laboratory)
Karan Shah (DSECOP Fellow, Center for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-Rossendorf)
Cunwei Fan (DSECOP Fellow, University of Illinois at Urbana Champaign)