Tucker Burgin

Tucker Burgin University of Michigan 2019-2020 Software Fellow Adviser: Heather B. Mayes MolSSI Software Mentor: Dr. Sam Ellis “Building software tools for understanding and evolving enzymes in silico guided by unbiased, all-atom simulations”

Madison Berger

Madison Berger University of North Texas 2020-2021 Software Fellow Adviser: Prof. Andres Cisneros MolSSI Software Mentor: Dr. Jessica A. Nash “Implementation of advanced potentials for QM/MM calculations and application to mutation impacts in protein complexes.”

Dominic Rufa

Dominic Rufa Weill Cornell Graduate School of Medical Sciences Adviser: Prof. John D. Chodera MolSSI Software Mentor: “Development of Python modules for continuum-embedding, integrated “Development of hybrid machine learning/molecular mechanics-based simulation and free energy calculation software for accurate molecular property predictions”

Isabela Quintela

LinkedIn Isabela Quintela Matos Cornell University Adviser: Prof. Fernando Escobedo MolSSI Software Mentor: “Development of Python modules for continuum-embedding, integrated “Development of free-energy-based extrapolation methods to optimize Hamiltonian’s parameters that stabilize sought-after mesophases in nanoparticle systems”

Linqing Peng

Linqing Peng California Institute of Technology Adviser: Prof. Garnet K. Chan MolSSI Software Mentor: “Creation of a general, open-sourced implementation of density matrix embedding framework to predict correlated properties with both high accuracy and affordable cost”

Heejune Park

View on GitHub Heejune Park University of California, Davis Adviser: Prof. Lee-Ping Wang MolSSI Software Mentor: “Development of reaction path finding and optimization methods and implementation into the QCArchive Infrastructure”

Aria Hosseini

Aria Hosseini Massachusetts Institute of Technology Adviser: Profs. Giuseppe Romano and Keith A. Nelson MolSSI Software Mentor: “Development of a package, called OpenKapitza, will wrap around molecular dynamics and density functional theory codes to compute heat transport across inhomogeneous interfaces”

Chenru Duan

View Website View on GitHub Chenru Duan Massachusetts Institute of Technology Adviser: Prof. Heather Kulik MolSSI Software Mentor: “Integrating machine learning in the process of quantum chemistry calculations to improve the efficiency and accuracy for high throughput computation, one of the most vital steps for fruitful materials discovery.”

Cody Drisko

View on GitHub Cody Drisko University of Notre Dame Adviser: Prof. J. Daniel Gezelter MolSSI Software Mentor: “Increasing the accessibility of reverse non-equilibrium molecular dynamics (RNEMD) algorithms for the efficient calculation of select transport properties”

Edan Bainglass

View on GitHub Edan Bainglass University of North Texas Adviser: Prof. Oliviero Andreussi MolSSI Software Mentor: “Development of Python modules for continuum-embedding, integrated quantum-embedding, and multi-scale simulation automation and optimization”