Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era. - Gabrielle Allen; Igor Andreoni; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; Zachariah B. Etienne; Daniel George; et al. (CoRR, 2019)

Enabling real-time multi-messenger astrophysics discoveries with deep learning. - Eliu A. Huerta; Gabrielle Allen; Igor Andreoni; Javier Mauricio Antelis; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; et al. (CoRR, 2019)

ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing. - Ahmed Elnaggar; Michael Heinzinger; Christian Dallago; Ghalia Rehawi; Yu Wang; Llion Jones; Tom Gibbs; Tamas Feher; Christoph Angerer; Martin Steinegger; Debsindhu Bhowmik; Burkhard Rost (CoRR, 2020)

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. - Aymen Al Saadi; Dario Alfè; Yadu N. Babuji; Agastya Bhati; Ben Blaiszik; Alexander Brace; Thomas S. Brettin; Kyle Chard; Ryan Chard; Austin Clyde; Peter V. Coveney; Ian T. Foster; et al. (ICPP, 2021)

Enabling ISO Standard Languages for Complex HPC Workflows. - M. Graham Lopez; Jeff R. Hammond; Jack C. Wells; Tom Gibbs; Timothy B. Costa (SMC, 2021)

NVIDIA's Cloud Native Supercomputing. - Gilad Shainer; Richard L. Graham; Chris J. Newburn; Oscar R. Hernandez; Gil Bloch; Tom Gibbs; Jack C. Wells (SMC, 2021)

CodeTrans: Towards Cracking the Language of Silicone's Code Through Self-Supervised Deep Learning and High Performance Computing. - Ahmed Elnaggar; Wei Ding; Llion Jones; Tom Gibbs; Tamas Feher; Christoph Angerer; Silvia Severini; Florian Matthes; Burkhard Rost (CoRR, 2021)

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. - Lorenzo Casalino; Abigail C. Dommer; Zied Gaieb; Emília P. Barros; Terra Sztain; Surl-Hee Ahn; Anda Trifan; Alexander Brace; Anthony T. Bogetti; Austin Clyde; Heng Ma; Hyungro Lee; et al. (Int. J. High Perform. Comput. Appl., 2021)

AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. - Jeyan Thiyagalingam; Gregor von Laszewski; Junqi Yin; Murali Emani; Juri Papay; Gregg Barrett; Piotr Luszczek; Aristeidis Tsaris; Christine R. Kirkpatrick; Feiyi Wang; Tom Gibbs; Venkatram Vishwanath; et al. (ISC Workshops, 2022)

Performance Evaluation and Acceleration of the QTensor Quantum Circuit Simulator on GPUs. - Danylo Lykov; Angela Chen; Huaxuan Chen; Kristopher Keipert; Zheng Zhang; Tom Gibbs; Yuri Alexeev (CoRR, 2022)

Accelerating IceCube's Photon Propagation Code with CUDA. - Hendrik Schwanekamp; Ramona Hohl; Dmitry Chirkin; Tom Gibbs; Alexander Harnisch; Claudio Kopper; Peter Messmer; Vishal Mehta; Alexander R. Olivas; Benedikt Riedel; Martin Rongen; David Schultz; et al. (Comput. Softw. Big Sci., 2022)

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. - Anda Trifan; Defne Gorgun; Michael Salim; Zongyi Li; Alexander Brace; Maxim Zvyagin; Heng Ma; Austin Clyde; David Clark; David J. Hardy; Tom Burnley; Lei Huang 019; et al. (Int. J. High Perform. Comput. Appl., 2022)

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning. - Ahmed Elnaggar; Michael Heinzinger; Christian Dallago; Ghalia Rehawi; Yu Wang; Llion Jones; Tom Gibbs; Tamas Feher; Christoph Angerer; Martin Steinegger; Debsindhu Bhowmik; Burkhard Rost (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. - Abigail C. Dommer; Lorenzo Casalino; Fiona L. Kearns; Mia A. Rosenfeld; Nicholas Wauer; Surl-Hee Ahn; John Russo 003; A. Sofia F. Oliveira; Clare Morris; Anthony T. Bogetti; Anda Trifan; Alexander Brace; et al. (Int. J. High Perform. Comput. Appl., 2023)

AI-Augmented Facilities: Bridging Experiment and Simulation with ML (Dagstuhl Seminar 23132). - Peer-Timo Bremer; Brian K. Spears; Tom Gibbs; Michael Bussmann (Dagstuhl Reports, 2023)

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. - Gautham Dharuman; Kyle Hippe; Alexander Brace; Sam Foreman; Väinö Hatanpää; Varuni Katti Sastry; Huihuo Zheng; Logan T. Ward; Servesh Muralidharan; Archit Vasan; Bharat Kale; Carla M. Mann; et al. (SC, 2024)

Emerging Vulnerabilities in Frontier Models: Multi-Turn Jailbreak Attacks. - Tom Gibbs; Ethan Kosak-Hine; George Ingebretsen; Jason Zhang; Julius Broomfield; Sara Pieri; Reihaneh Iranmanesh; Reihaneh Rabbany; Kellin Pelrine (CoRR, 2024)

A Simulation System Towards Solving Societal-Scale Manipulation. - Maximilian Puelma Touzel; Sneheel Sarangi; Austin Welch; Gayatri Krishnakumar; Dan Zhao; Zachary Yang; Hao Yu; Ethan Kosak-Hine; Tom Gibbs; Andreea Musulan; Camille Thibault; Busra Tugce Gurbuz; et al. (CoRR, 2024)

Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows. - Rafael Ferreira da Silva; Deborah Bard; Kyle Chard; Shaun De Witt; Ian T. Foster; Tom Gibbs; Carole A. Goble; William F. Godoy; Johan Gustafsson 001; Utz-Uwe Haus; Stephen Hudson; Shantenu Jha; et al. (CoRR, 2024)

The Structural Safety Generalization Problem. - Julius Broomfield; Tom Gibbs; George Ingebretsen; Ethan Kosak-Hine; Tia Nasir; Jason Zhang; Reihaneh Iranmanesh; Sara Pieri; Reihaneh Rabbany; Kellin Pelrine (ACL (Findings), 2025)

Online Influence Campaigns: Strategies and Vulnerabilities. - Andreea Musulan; Veronica Xia; Ethan Kosak-Hine; Tom Gibbs; Vidya Sujaya; Reihaneh Rabbany; Jean-François Godbout; Kellin Pelrine (CoRR, 2025)

MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow. - Xiaoli Yan; Nathaniel Hudson; Hyun Park; Daniel Grzenda; J. Gregory Pauloski; Marcus Schwarting; Haochen Pan; Hassan Harb; Sam Foreman; Chris Knight 001; Tom Gibbs; Kyle Chard; et al. (CoRR, 2025)