Description: This workshop will provide an overview of machine learning tools applied to study molecular systems with a focus on computational molecular science. It will feature a mix of lectures and hands-on exercises running machine learning algorithms with molecular simulations on national supercomputing resources. The workshop will include a session on diversity, equity, and inclusion aspects of computational sciences. Sessions will be taught in Software Carpentry style, with approximately equal time divided between lectures and hands-on programming exercises.

Registration: The application for the workshop can be accessed here.

Expected number of participants: 40

Equipment Needed: Students will need a laptop and have Jupyter notebooks installed. Computing resources for performing exercises will be provided in Bridges-2 at PSC.

Eligibility: Participation is limited to graduate students, undergraduate students (with junior or senior standing), postdoctoral, early career faculty, with some experience in molecular simulations and Python scripting. Applicants must be associated with an US based educational institution, national lab, or industry.

Registration Fee: The registration fee will be waived for participants from non-PhD-granting and primary undergraduate institutions (PUIs).

Financial Support: Financial support is available to cover housing (in university dormitory) for some non-local participants. A limited number of travel stipends (up to $500) are available to help broaden participation.

Organizers/Instructors:

• Yamil Colón, Notre Dame University
• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota Twin Cities
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado, Boulder
• Shuwen Yue, Cornell University

Description: This workshop will provide an overview of machine learning applied to molecules and materials systems. It will feature of mix of lectures and hands-on interactive exercises in Python. The session will run for five days, 3 hours a day, 3-6 EDT / 2-5 CDT / 1-4 MDT / 12-3 PDT.

Registration: The registration form for the workshop is at: https://forms.gle/42Vzmw13F9HtJfaNA. Deadline for registration April 21, 2025.

Preliminary Schedule

• Monday, April 28th
  • Review of machine learning concepts
• Tuesday, April 29th
  • Molecular featurization and representations for machine learining
• Wednesday, April 30th
  • Neural nets and graph neural nets in pytorch
• Thursday, May 1st
  • Active Learning for molecular design
• Friday, May 2nd
  • Generative modeling for molecules

Eligibility: Graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty. The expectation is that students will have some experience in Python and ML.

Registration Fee: None

Financial Aid: N/A

Expected number of participants: 100

Equipment Needed: Students will need laptops or desktops that can both access Zoom and have Jupyter notebooks installed. Computing resources for performing exercises will be on Google Colab

Organizers/Instructors

• Camille Bilodeau, University of Virginia
• Yamil Colon, University of Notre Dame
• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado Boulder
• Shuwen Yue, Cornell University

Description: Molecular dynamics (MD) simulation techniques have become an essential tools in understanding thermophysical and equilibrium properties of systems ranging from organic liquids to ionic liquids, polymers, biomolecules, solutions, zeolites, metal organic frameworks and covalent organic frameworks, etc. This course will focus on the theoretical underpinnings of MD simulations, statistical mechanics principles, and practical tools and techniques for setting up and computing macroscopic properties. Open-source MD engines including GROMACS and HOOMD will be used to demonstrate fundamental concepts.

Eligibility: graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty, and relevant industry. Apply here

Registration Fee: $150 (waived for participants from non-PhD granting institutes) after application.

Financial Aid: Financial support is available to cover housing (in university dormitory), meals, and parking cost for all non-local participants. A limited number of travel stipends ($500) are available to help broaden participation.

Expected number of participants: 40

Tranportation:

• Nearest Airport: Boise, BOI; Uber/Lyft transportation to the University (5 minutes)

Equipment Needed: Students will need a laptop.

Organizers/Instructors

• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado Boulder
• Amir Haji-Akbari, Yale University
• Rachael Skye, Cornell University (Dshemuchadse lab)
• Hemanth Haridas, University of Utah (Clark Lab)

Description: This workshop will provide an overview of modern enhanced sampling algorithms, including replica exchange, umbrella sampling, metadynamics, and path sampling methods. It will feature of mix of lectures and hands-on exercises running GROMACS on national supercomputing resources, and will run for 3 hours each day. The workshop will include a session on diversity, equity, and inclusion aspects of computational sciences. The session will run for five days, 3-6 EDT / 2-5 CDT / 1-4 MDT / 12-3 PDT. Note that the workshop will be similar (though not exactly the same) as last years’ workshop, whose material is posted here for reference: https://github.com/icomse/3rd_workshop_advanced_sampling

Registration: The application for the workshop is at: https://forms.gle/rzR5aJ5cPhFraQ4i6.

Preliminary Schedule

• Monday, February 12th
  • Free energy, probability, and sampling theory
  • Expanded ensemble simulations
  • Diversity, equity and inclusion in computational science
• Tuesday, February 13th
  • Metadynamics
• Wednesday, February 14th
  • Running coupled simulations on HPC resources
  • Temperature and Hamiltonian replica exchange simulations
• Thursday, February 15th
  • Transition path sampling
  • Forward flux sampling
• Friday, February 16th
  • Exploring combinations and applications
  • Wrapup

Eligibility: Graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty. The expectation is that students will have some experience in molecular simulation and Python scripting. Attendees must be at a U.S. institution.

Registration Fee: None

Financial Aid: N/A

Expected number of participants: 50

Equipment Needed: Students will need laptops or desktops that can both access Zoom and have Jupyter notebooks installed. Computing resources for performing exercises will be provided.

Organizers/Instructors

• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado Boulder
• Omar Valsson, University of North Texas

Description: This workshop will provide an overview of machine learning tools applied to study molecular systems with a focus on computational molecular science. It will feature a mix of lectures and hands-on exercises running machine learning algorithms with molecular simulations on national supercomputing resources. The workshop will include a session on diversity, equity, and inclusion aspects of computational sciences. Sessions will be taught in Software Carpentry style, with approximately equal time divided between lectures and hands-on programming exercises.

Registration: The application for the workshop can be accessed here

Preliminary Schedule:

• Monday July 10th, 2023
  • Feature representation
  • Dimensionality reduction
  • Unsupervised learning
• Tuesday, July 11th, 2023
  • Clustering and visualization
  • Regression and supervised learning
  • Training, testing, and validation
  • Simple regression models
  • D&I workshop
• Wednesday, July 12th, 2023
  • Structured vs unstructured data
  • Regularized vs tree based methods
  • Interpretability
  • Workshop Outing
• Thursday, July 13th, 2023
  • Deep learning
  • Advanced examples of ML applications to molecular science
  • ML on cyberinfrastructure
• Friday, July 14th, 2023
  • Generative models and inverse design
  • General Q&A
  • Wrap up

Expected number of participants: 40

Equipment Needed: Students will need a laptop and have Jupyter notebooks installed. Computing resources for performing exercises will be provided in Bridges-2 at PSC.

Dormitory Check-In: July 9th, 2023 (starts at 1 pm) and Check out: July 14th 2023 (by noon)

Eligibility: Participation is limited to graduate students, undergraduate students (with junior or senior standing), postdoctoral, early career faculty, with some experience in molecular simulations and Python scripting. Applicants must be associated with an US based educational institution, national lab, or industry.

Registration Fee: None for academic participants

Financial Support: Financial support is available to cover housing (in university dormitory), meals, and parking cost for all non-local participants. A limited number of travel stipends (up to $500) are available to help broaden participation.

Organizers/Instructors:

• Chris Bartel, University of Minnesota Twin Cities
• Rose Cersonsky, University of Wisconsin-Madison
• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota Twin Cities
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado, Boulder

Description: This workshop will provide an overview of density functional theory and its applications in chemical and materials science. It will feature a mix of lectures and hands-on exercises running electronic structure codes on national supercomputing resources. The workshop will include a session on diversity, equity, and inclusion aspects of computational sciences. Sessions will be taught in Software Carpentry style, with approximately equal time divided between lectures and hands-on exercises running and analyzing simulations.

Registration: The application for the workshop is can be accessed here

Preliminary Schedule:

• Monday, June 5th
  • Fundamentals of electronic structure theory
  • Elements of density functional theory (functional hierarchy)
  • Diversity, equity and inclusion in computational science
• Tuesday, June 6th
  • Ground state electronic properties (gas phase/isolated molecules)
  • Running coupled simulations on HPC resources
  • Applications in chemical catalysis
• Wednesday, June 7th
  • Range separated functionals
  • IP tuning
  • Gap renormalization (medium effects)
• Thursday, June 8th
  • Applications in materials science (electronic and optical properties)
  • Excited state properties
• Friday, June 9th
  • Hands-projects based on attendee interests
  • General Q/A
  • Wrapup

Eligibility: Participation is limited to graduate students, undergraduate students (with junior or senior standing), postdoctoral, early career faculty, with some experience in DFT calculations and Python scripting. Applicants must be associated with an US based educational institution, national lab, or industry.

Registration Fee: None

Financial support: Financial support is available to cover housing (in university dormitory), meals, and parking cost for all non-local participants. A limited number of travel stipends (up to $500) are available to help broaden participation.

Expected number of participants: 40

Equipment Needed: Students will need a laptop and have Jupyter notebooks installed. Computing resources for performing exercises will be provided in Bridges-2 at PSC.

Organizers/Instructors:

• Oliviero Andreussi, Boise State University
• John Herbert, Ohio State University
• Eric Jankowski, Boise State University
• Lan (Samantha) Li, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado, Boulder

Description: This workshop will provide an overview of modern enhanced sampling algorithms, including replica exchange, umbrella sampling, metadynamics, and path sampling methods. It will feature of mix of lectures and hands-on exercises running GROMACS on national supercomputing resources, and will run for 3 hours each day. The workshop will include a session on diversity, equity, and inclusion aspects of computational sciences. The session will run for five days, 3-6 EDT / 2-5 CDT / 1-4 MDT / 12-3 PDT.

Registration: The application for the workshop is at: https://forms.gle/LwJv5qHdA57fwJmN7.

Preliminary Schedule

• Monday, March 20th
  • Free energy, probability, and sampling theory
  • Expanded ensemble simulations
  • Diversity, equity and inclusion in computational science
• Tuesday, March 21st
  • Potentials of mean force
  • Metadynamics
• Wednesday, March 22nd
  • Running coupled simulations on HPC resources
  • Temperature and Hamiltonian replica exchange simulations
• Thursday, March 23rd
  • Transition path sampling
  • Transition interface sampling
• Friday, March 24th
  • Forward flux sampling
  • Exploring combinations and applications
  • Wrapup

Eligibility: Graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty. The expectation is that students will have some experience in molecular simulation and Python scripting. Attendees must be at a U.S. institution.

Registration Fee: None

Financial Aid: N/A

Expected number of participants: 50

Equipment Needed: Students will need laptops or desktops that can both access Zoom and have Jupyter notebooks installed. Computing resources for performing exercises will be provided.

Organizers/Instructors

• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado Boulder
• Omar Valsson, University of North Texas

Density functional theory (DFT) has become an essential tool for modeling chemical reactions due to its relatively low computational cost and favorable scaling with the system size. This course will present a theoretical and practical introduction to computational techniques for studying chemical catalysis and kinetics. Participants will learn practical aspects of DFT calculations and advanced topics such as the effect of solvation on chemical reactions. The open-source software CP2K will be used for the hands-on tutorial sessions.

Eligibility: graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty

Registration Fee: $100 (waived for participants from non-PhD granting institutes)

Financial Aid: Financial support is available to cover housing (in university dormitory), meals, and parking cost for all non-local participants. Limited number of travel stipends ($500) are available to help broaden participation.

Expected number of participants: 40

Directions to housing: N/A

Where to eat: N/A

Equipment Needed: Students are encouraged to bring their laptop.

Organizers/Instructors

• Mike Janik, Pennsylvania State University
• Eric Jankowski, Boise State University
• Andrew J. Medford, Georgia Institute of Technology
• Neeraj Rai, Mississippi State University

Tentative Schedule

June 12: Arrival/Check-in

June 13: Morning: Fundamentals of DFT Afternoon: Fundamentals of Catalysis Evening: Free

June 14: Morning: Introduction to Linux/HPC/CP2K Afternoon: Diversity/Inclusion workshop Evening: HPC/computer set up/computational housekeeping

June 15: Morning-I: Practical aspects of DFT calculations Morning-II: Surfaces/Binding Energy/Vibrational Frequencies Afternoon: Hands-on session Evening: Poster Session

June 16: Morning: Activation Energy, Microkinetics, Rate Expressions Afternoon: Hands-on session Evening: Invited Talk

June 17: Morning: Solvation/Electrochemistry Afternoon: Hand-on session

June 18: Morning: Special Topics/Open Project Discussions Afternoon: Depart

Description: Monte Carlo (MC) and molecular dynamics (MD) simulation techniques have become essential tools in understanding thermophysical and phase equilibria properties of systems ranging from organic liquids to ionic liquids, polymers, biomolecules, solutions, zeolites, metal organic frameworks and covalent organic frameworks, etc. These techniques are based on statistical mechanics principles and enable one to access length scales spanning tens of nanometers and sample timescales up to hundreds of nanoseconds. This course will focus on the theoretical underpinnings of MC and MD simulations and techniques for computing macroscopic properties such as self-diffusion coefficients, ionic conductivity, viscosity, vapor-liquid equilibria and gas absorption/adsorption isotherms. The open-source software packages Gromacs and Cassandra will be used for the hands-on tutorial sessions.

Eligibility: graduate student, undergraduate student (with junior or senior standing), postdoctoral, early career faculty

Registration Fee: $100 (waived for participants from non-PhD granting institutes)

Financial Aid: Financial support is available to cover housing (in university dormitory), meals, and parking cost for all non-local participants. Limited number of travel stipends ($500) are available to help broaden participation.

Expected number of participants: 40

Tranportation:

• Nearest Airport: Stillwater, OK; Uber/Lyft transportation to the University (5 minutes)
• Alternate Airports: Oklahoma City, 75 miles, ~1 hr 15 mins, Tulsa, 75 miles, ~1 hr 15 mins

Equipment Needed: Students are encouraged to bring their laptop.

Organizers/Instructors

• Eric Jankowski, Boise State University
• Neeraj Rai, Mississippi State University
• Sapna Sarupria, University of Minnesota
• Jindal Shah, Oklahoma State University
• Michael Shirts, University of Colorado Boulder