Networking Materials Data: Accelerating Discovery at Experimental Facilities. - Ian T. Foster; Rachana Ananthakrishnan; Ben Blaiszik; Kyle Chard; Ray Osborn; Steven Tuecke; Michael Wilde; Justin M. Wozniak (High Performance Computing Workshop, 2014)

Big Data Remote Access Interfaces for Light Source Science. - Justin M. Wozniak; Kyle Chard; Ben Blaiszik; Ray Osborn; Michael Wilde; Ian T. Foster (BDC, 2015)

Globus Data Publication as a Service: Lowering Barriers to Reproducible Science. - Kyle Chard; Jim Pruyne; Ben Blaiszik; Rachana Ananthakrishnan; Steven Tuecke; Ian T. Foster (e-Science, 2015)

Software Defined Cyberinfrastructure. - Ian T. Foster; Ben Blaiszik; Kyle Chard; Ryan Chard (ICDCS, 2017)

Globus Platform Services for Data Publication. - Rachana Ananthakrishnan; Ben Blaiszik; Kyle Chard; Ryan Chard; Brendan McCollam; Jim Pruyne; Stephen Rosen; Steven Tuecke; Ian T. Foster (PEARC, 2018)

DLHub: Model and Data Serving for Science. - Ryan Chard; Zhuozhao Li; Kyle Chard; Logan T. Ward; Yadu N. Babuji; Anna Woodard; Steven Tuecke; Ben Blaiszik; Michael J. Franklin; Ian T. Foster (IPDPS, 2019)

Serverless Workflows for Indexing Large Scientific Data. - Tyler J. Skluzacek; Ryan Chard; Ryan Wong 002; Zhuozhao Li; Yadu N. Babuji; Logan T. Ward; Ben Blaiszik; Kyle Chard; Ian T. Foster (WOSC@Middleware, 2019)

Petrel: A Programmatically Accessible Research Data Service. - William E. Allcock; Benjamin S. Allen; Rachana Ananthakrishnan; Ben Blaiszik; Kyle Chard; Ryan Chard; Ian T. Foster; Lukasz Lacinski; Michael E. Papka; Rick Wagner (PEARC, 2019)

Publishing and Serving Machine Learning Models with DLHub. - Ryan Chard; Logan T. Ward; Zhuozhao Li; Yadu N. Babuji; Anna Woodard; Steven Tuecke; Kyle Chard; Ben Blaiszik; Ian T. Foster (PEARC, 2019)

Serverless Supercomputing: High Performance Function as a Service for Science. - Ryan Chard; Tyler J. Skluzacek; Zhuozhao Li; Yadu N. Babuji; Anna Woodard; Ben Blaiszik; Steven Tuecke; Ian T. Foster; Kyle Chard (CoRR, 2019)

funcX: A Federated Function Serving Fabric for Science. - Ryan Chard; Yadu N. Babuji; Zhuozhao Li; Tyler J. Skluzacek; Anna Woodard; Ben Blaiszik; Ian T. Foster; Kyle Chard (HPDC, 2020)

Towards Online Steering of Flame Spray Pyrolysis Nanoparticle Synthesis. - Maksim Levental; Ryan Chard; Joseph A. Libera; Kyle Chard; Aarthi Koripelly; Jakob R. Elias; Marcus Schwarting; Ben Blaiszik; Marius Stan; Santanu Chaudhuri; Ian T. Foster (XLOOP@SC, 2020)

Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. - Yadu N. Babuji; Ben Blaiszik; Tom Brettin; Kyle Chard; Ryan Chard; Austin Clyde; Ian T. Foster; Zhi Hong; Shantenu Jha; Zhuozhao Li; Xuefeng Liu; Arvind Ramanathan; et al. (CoRR, 2020)

The Data Station: Combining Data, Compute, and Market Forces. - Raul Castro Fernandez; Kyle Chard; Ben Blaiszik; Sanjay Krishnan; Aaron J. Elmore; Ziad Obermeyer; Josh Risley; Sendhil Mullainathan; Michael J. Franklin; Ian T. Foster (CoRR, 2020)

HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data. - Sutanay Choudhury; Jenna A. Bilbrey; Logan T. Ward; Sotiris S. Xantheas; Ian T. Foster; Joseph P. Heindel; Ben Blaiszik; Marcus E. Schwarting (CoRR, 2020)

Confluence of Artificial Intelligence and High Performance Computing for Accelerated, Scalable and Reproducible Gravitational Wave Detection. - Eliu A. Huerta; Asad Khan; Xiaobo Huang; Minyang Tian; Maksim Levental; Ryan Chard; Wei Wei 021; Maeve Heflin; Daniel S. Katz; Volodymyr V. Kindratenko; Dawei Mu; Ben Blaiszik; et al. (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)

AI- and HPC-enabled Lead Generation for SARS-CoV-2: Models and Processes to Extract Druglike Molecules Contained in Natural Language Text. - Zhi Hong; J. Gregory Pauloski; Logan T. Ward; Kyle Chard; Ben Blaiszik; Ian T. Foster (CoRR, 2021)

Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. - Austin Clyde; Thomas S. Brettin; Alexander Partin; Hyun Seung Yoo; Yadu N. Babuji; Ben Blaiszik; André Merzky; Matteo Turilli; Shantenu Jha; Arvind Ramanathan; Rick Stevens (CoRR, 2021)

DLHub: Simplifying publication, discovery, and use of machine learning models in science. - Zhuozhao Li; Ryan Chard; Logan T. Ward; Kyle Chard; Tyler J. Skluzacek; Yadu N. Babuji; Anna Woodard; Steven Tuecke; Ben Blaiszik; Michael J. Franklin; Ian T. Foster (J. Parallel Distributed Comput., 2021)

Linking Scientific Instruments and HPC: Patterns, Technologies, Experiences. - Rafael Vescovi; Ryan Chard; Nickolaus D. Saint; Ben Blaiszik; Jim Pruyne; Tekin Bicer; Alex Lavens; Zhengchun Liu; Michael E. Papka; Suresh Narayanan; Nicholas Schwarz; Kyle Chard; et al. (CoRR, 2022)

3D Convolutional Neural Networks for Dendrite Segmentation Using Fine-Tuning and Hyperparameter Optimization. - Jim James; Nathan Pruyne; Tiberiu Stan; Marcus Schwarting; Jiwon Yeom; Seungbum Hong; Peter Voorhees; Ben Blaiszik; Ian T. Foster (CoRR, 2022)

FAIR principles for AI models, with a practical application for accelerated high energy diffraction microscopy. - Nikil Ravi; Pranshu Chaturvedi; Eliu A. Huerta; Zhengchun Liu; Ryan Chard; Aristana Scourtas; K. J. Schmidt; Kyle Chard; Ben Blaiszik; Ian T. Foster (CoRR, 2022)

funcX: Federated Function as a Service for Science. - Zhuozhao Li; Ryan Chard; Yadu N. Babuji; Ben Galewsky; Tyler J. Skluzacek; Kirill Nagaitsev; Anna Woodard; Ben Blaiszik; Josh Bryan; Daniel S. Katz; Ian T. Foster; Kyle Chard (CoRR, 2022)

FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. - Eliu A. Huerta; Ben Blaiszik; L. Catherine Brinson; Kristofer E. Bouchard; Daniel Diaz 003; Caterina Doglioni; Javier M. Duarte; Murali Emani; Ian T. Foster; Geoffrey C. Fox; Philip C. Harris; Lukas Heinrich; et al. (CoRR, 2022)

High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. - Austin Clyde; Stephanie Galanie; Daniel W. Kneller; Heng Ma; Yadu N. Babuji; Ben Blaiszik; Alexander Brace; Thomas S. Brettin; Kyle Chard; Ryan Chard; Leighton Coates; Ian T. Foster; et al. (J. Chem. Inf. Model., 2022)

Linking scientific instruments and computation: Patterns, technologies, and experiences. - Rafael Vescovi; Ryan Chard; Nickolaus D. Saint; Ben Blaiszik; Jim Pruyne; Tekin Bicer; Alex Lavens; Zhengchun Liu; Michael E. Papka; Suresh Narayanan; Nicholas Schwarz; Kyle Chard; et al. (Patterns, 2022)

$f$funcX: Federated Function as a Service for Science. - Zhuozhao Li; Ryan Chard; Yadu N. Babuji; Ben Galewsky; Tyler J. Skluzacek; Kirill Nagaitsev; Anna Woodard; Ben Blaiszik; Josh Bryan; Daniel S. Katz; Ian T. Foster; Kyle Chard (IEEE Trans. Parallel Distributed Syst., 2022)

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. - Nathaniel Hudson; J. Gregory Pauloski; Matt Baughman; Alok Kamatar; Mansi Sakarvadia; Logan T. Ward; Ryan Chard; André Bauer 001; Maksim Levental; Wenyi Wang; Will Engler; Owen Price Skelly; et al. (BDCAT, 2023)

Active Research Data Management with the Django Globus Portal Framework. - Nickolaus D. Saint; Ryan Chard; Rafael Vescovi; Jim Pruyne; Ben Blaiszik; Rachana Ananthakrishnan; Michael E. Papka; Rick Wagner; Kyle Chard; Ian T. Foster (PEARC, 2023)

Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy. - Sergei V. Kalinin; Debangshu Mukherjee; Kevin M. Roccapriore; Ben Blaiszik; Ayana Ghosh; Maxim A. Ziatdinov; Anees Al-Najjar; Christina Doty; Sarah Akers; Nageswara S. V. Rao; Joshua C. Agar; Steven R. Spurgeon (CoRR, 2023)

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon. - Kevin Maik Jablonka; Qianxiang Ai; Alexander Al-Feghali; Shruti Badhwar; Joshua D. Bocarsly; Andres M. Bran; Stefan Bringuier; L. Catherine Brinson; Kamal Choudhary; Defne Circi; Sam Cox; Wibe A. de Jong; et al. (CoRR, 2023)

Towards a Modular Architecture for Science Factories. - Rafael Vescovi; Tobias Ginsburg; Kyle Hippe; Doga Ozgulbas; Casey Stone; Abraham Stroka; Rory Butler; Ben Blaiszik; Tom Brettin; Kyle Chard; Mark Hereld; Arvind Ramanathan; et al. (CoRR, 2023)

Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning. - Logan T. Ward; Ben Blaiszik; Cheng-Wei Lee 006; Troy Martin; Ian T. Foster; André Schleife (CoRR, 2023)

Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? - Marcus Schwarting; Nathan A. Seifert; Michael J. Davis; Ben Blaiszik; Ian T. Foster; Kirill Prozument (CoRR, 2024)

Foundry-ML (latest). - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (J. Open Source Softw., 2024)

A practical guide to machine learning interatomic potentials - Status and future. - Ryan Jacobs; Dane Morgan; Siamak Attarian; Jun Meng; Chen Shen; Zhenghao Wu; Clare Yijia Xie; Julia H. Yang; Nongnuch Artrith; Ben Blaiszik; Gerbrand Ceder; Kamal Choudhary; et al. (CoRR, 2025)

34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery. - Yoel Zimmermann; Adib Bazgir; Alexander Al-Feghali; Mehrad Ansari; Joshua D. Bocarsly; L. Catherine Brinson; Yuan Chiang; Defne Circi; Min-Hsueh Chiu; Nathan Daelman; Matthew L. Evans; Abhijeet Sadashiv Gangan; et al. (CoRR, 2025)