Accelerating Curricular Transformation in the Computational Molecular Sciences Faculty Fellowship


The Molecular Sciences Software Institute (MolSSI) is pleased to announce the launch of a new education and faculty development program: Accelerating Curricular Transformation in the Computational Molecular Sciences (ACT-CMS). The goal of ACT-CMS is to transform science curricula by accelerating the integration of programming and computation into existing molecular science courses through faculty training and the development of open and reusable curricular modules.

ACT-CMS will achieve this goal by providing faculty with the training and resources needed to integrate programming and computation into their existing courses. ACT-CMS is generously funded by the National Science Foundation Training-based Workforce Development for Advanced Cyberinfrastructure program (OAC 2321044,OAC 2321045).

For more information about the ACT-CMS fellowship program, please visit the ACT-CMS website.

Meet our faculty fellows!

Congratulations to our MolSSI Faculty Fellows! These molecular science educators will collaborate with MolSSI to integrate programming, data competency, and computing into their curriculum. ACT-CMS Fellows convene with us each year for a week-long Curriculum Development Bootcamp.

2025-2027 Faculty Fellows

William Ames

Juniata College

Modeling the kinetics of reactions in Python with QM calculated transition state energies. 

Keith Fraser

Rensselaer Polytechnic Institute

Structural Bioinformatics

Robin Grotjahn

Santa Clara University

High Performance Computing Applications in a General Chemistry Laboratory

Heidi Hendrickson

Lafayette College

Modules for quantum information science in physical chemistry

Linlin Jensen

The Pennsylvania State University

Data Analysis and Visualization with AI-enhanced Programming in General Chemistry Courses

Prajay Patel

University of Dallas

Transitioning from Excel to Python for Inquiry-Based Data Analysis in Physical Chemistry Labs

Craig Smith

Washington University in St. Louis

Interactive Protein Structure Analysis Using Jupyter Notebooks

Nik Tsotakos

The Pennsylvania State University

Modeling the effects of mutations population-wide using Python

Cecilia Vollbrecht

Kalamazoo College

Visualization of Common Quantum Mechanical Models and Their Spectroscopy Applications Using Python

Wenwu Xu

San Diego State University

Transforming Materials Modeling Education through LLM-Assisted Coding and HPC Integration for SDSU’s First Independent Doctoral Engineering Program

2024-2026 Faculty Fellows

Lori Banks

Prairie View A&M University

Coding for Biological Research Training

Gergely Gidofalvi

Gonzaga University

The Rovibrational Spectrum of H^{35}Cl: Comparison Between Theory and Experiment

Kevin Greenman

Catholic Institute of Technology

Bridging Basic Chemistry and Cheminformatics: A Jupyter-based Module on Molecular Representation for Introductory Chemistry

Rachel Kurchin

Carnegie Mellon University

Diffusion Lab for Introductory Materials Science

Christine Morales

University of Mount Union

Python-based Jupyter notebooks in the analytical chemistry laboratory

Brandy Russell

Gustavus Adolphus College

Data analysis and visualization using Python in general chemistry

Steve Singleton

Coe College

Integrating Computing into the Physical Chemistry Curriculum Using a Guided-Inquiry Approach

Dom Sirianni

Daemen University

"Integrating" Symbolic Calculus into Biophysical Chemistry

Marc ter Horst

University of North Carolina in Chapel Hill

Organic Chemistry (grad level)

Marie van Staveren

University of Maryland, Baltimore County

Data Analysis Quick Pages for Experimental Physical Chemistry