Martini straight: Boosting performance using a shorter cutoff and GPUs. - Djurre H. De Jong; Svetlana Baoukina; Helgi I. Ingólfsson; Siewert J. Marrink (Comput. Phys. Commun., 2016)

A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer. - Francesco Di Natale; Harsh Bhatia; Timothy S. Carpenter; Chris Neale; Sara Kokkila Schumacher; Tomas Oppelstrup; Liam Stanton; Xiaohua Zhang; Shiv Sundram; Thomas R. W. Scogland; Gautham Dharuman; Michael P. Surh; et al. (SC, 2019)

Comparing GPU Power and Frequency Capping: A Case Study with the MuMMI Workflow. - Tapasya Patki; Zachary Frye; Harsh Bhatia; Francesco Di Natale; James N. Glosli; Helgi I. Ingólfsson; Barry Rountree (WORKS@SC, 2019)

Flux: Overcoming scheduling challenges for exascale workflows. - Dong H. Ahn; Ned Bass; Albert Chu; Jim Garlick; Mark Grondona; Stephen Herbein; Helgi I. Ingólfsson; Joseph Koning; Tapasya Patki; Thomas R. W. Scogland; Becky Springmeyer; Michela Taufer (Future Gener. Comput. Syst., 2020)

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning. - W. F. Drew Bennett; Stewart He; Camille L. Bilodeau; Derek Jones; Delin Sun; Hyojin Kim 001; Jonathan E. Allen; Felice C. Lightstone; Helgi I. Ingólfsson (J. Chem. Inf. Model., 2020)

Generalizable coordination of large multiscale workflows: challenges and learnings at scale. - Harsh Bhatia; Francesco Di Natale; Joseph Y. Moon; Xiaohua Zhang; Joseph R. Chavez; Fikret Aydin; Christopher B. Stanley; Tomas Oppelstrup; Chris Neale; Sara Kokkila Schumacher; Dong H. Ahn; Stephen Herbein; et al. (SC, 2021)

Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations. - Harsh Bhatia; Timothy S. Carpenter; Helgi I. Ingólfsson; Gautham Dharuman; Piyush Karande; Shusen Liu 001; Tomas Oppelstrup; Chris Neale; Felice C. Lightstone; Brian Van Essen; James N. Glosli; Peer-Timo Bremer (Nat. Mach. Intell., 2021)

Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints. - Konstantia Georgouli; Helgi I. Ingólfsson; Fikret Aydin; Mark Heimann; Felice C. Lightstone; Peer-Timo Bremer; Harsh Bhatia (CoRR, 2022)

Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning. - Fikret Aydin; Konstantia Georgouli; Gautham Dharuman; James N. Glosli; Felice C. Lightstone; Helgi I. Ingólfsson; Peer-Timo Bremer; Harsh Bhatia (CoRR, 2022)

A biology-informed similarity metric for simulated patches of human cell membrane. - Harsh Bhatia; Jayaraman J. Thiagarajan; Rushil Anirudh; T. S. Jayram; Tomas Oppelstrup; Helgi I. Ingólfsson; Felice C. Lightstone; Peer-Timo Bremer (Mach. Learn. Sci. Technol., 2022)

Machine Learning-driven Multiscale MD Workflows: The Mini-MuMMI Experience. - Loïc Pottier; Konstantia Georgouli; Timothy S. Carpenter; Fikret Aydin; Jeremy O. B. Tempkin; Dwight V. Nissley; Frederick H. Streitz; Thomas R. W. Scogland; Peer-Timo Bremer; Felice C. Lightstone; Helgi I. Ingólfsson (CoRR, 2025)