BOSS-LDG: A Novel Computational Framework That Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery. - Eliu A. Huerta; Roland Haas; Edgar Fajardo Hernandez; Daniel S. Katz; Stuart Anderson; Peter Couvares; Josh Willis 002; Timothy Bouvet; Jeremy Enos; William T. C. Kramer; Hon Wai Leong; David Wheeler (eScience, 2017)

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics. - Daniel George; Eliu A. Huerta (CoRR, 2017)

Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO. - Daniel George; Hongyu Shen; Eliu A. Huerta (CoRR, 2017)

Python Open Source Waveform Extractor (POWER): An open source, Python package to monitor and post-process numerical relativity simulations. - Daniel Johnson 003; Eliu A. Huerta; Roland Haas (CoRR, 2017)

Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Advanced LIGO Data. - Daniel George; Eliu A. Huerta (CoRR, 2017)

ENIGMA: Eccentric, Non-spinning, Inspiral Gaussian-process Merger Approximant for the characterization of eccentric binary black hole mergers. - Eliu A. Huerta; C. J. Moore; Prayush Kumar; Daniel George; Alvin J. K. Chua; Roland Haas; Erik Wessel; Daniel Johnson 003; Derek Glennon; Adam Rebei; A. Miguel Holgado; Jonathan R. Gair; et al. (CoRR, 2017)

Glitch Classification and Clustering for LIGO with Deep Transfer Learning. - Daniel George; Hongyu Shen; Eliu A. Huerta (CoRR, 2017)

Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation with Advanced LIGO Data. - Daniel George; Eliu A. Huerta (CoRR, 2017)

Denoising Gravitational Waves using Deep Learning with Recurrent Denoising Autoencoders. - Hongyu Shen; Daniel George; Eliu A. Huerta; Zhizhen Zhao 001 (CoRR, 2017)

Container solutions for HPC Systems: A Case Study of Using Shifter on Blue Waters. - Maxim Belkin; Roland Haas; Galen Wesley Arnold; Hon Wai Leong; Eliu A. Huerta; David Lesny; Mark S. Neubauer (PEARC, 2018)

Real-time regression analysis with deep convolutional neural networks. - Eliu A. Huerta; Daniel George; Zhizhen Zhao 001; Gabrielle Allen (CoRR, 2018)

Unsupervised learning and data clustering for the construction of Galaxy Catalogs in the Dark Energy Survey. - Asad Khan; Eliu A. Huerta; Sibo Wang 005; Robert A. Gruendl (CoRR, 2018)

Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-encoders. - Hongyu Shen; Daniel George; Eliu A. Huerta; Zhizhen Zhao 001 (ICASSP, 2019)

The Physics of Eccentric Binary Black Hole Mergers. A Numerical Relativity Perspective. - Eliu A. Huerta; Roland Haas; Sarah Habib; Anushri Gupta; Adam Rebei; Vishnu Chavva; Daniel Johnson 003; Shawn Rosofsky; Erik Wessel; Bhanu Agarwal; Diyu Luo; Wei Ren (CoRR, 2019)

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)

Deep Learning at Scale for Gravitational Wave Parameter Estimation of Binary Black Hole Mergers. - Hongyu Shen; Eliu A. Huerta; Zhizhen Zhao 001 (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)

Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms. - Arjun Gupta; Eliu A. Huerta; Zhizhen Zhao 001; Issam Moussa (CoRR, 2019)

Supporting High-Performance and High-Throughput Computing for Experimental Science. - Eliu A. Huerta; Roland Haas; Shantenu Jha; Mark S. Neubauer; Daniel S. Katz (Comput. Softw. Big Sci., 2019)

Physics-inspired deep learning to characterize the signal manifold of quasi-circular, spinning, non-precessing binary black hole mergers. - Asad Khan; Eliu A. Huerta; Arnav Das 001 (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)

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure. - Eliu A. Huerta; Asad Khan; Edward Davis; Colleen Bushell; William D. Gropp; Daniel S. Katz; Volodymyr V. Kindratenko; Seid Koric; William T. C. Kramer; Brendan McGinty; Kenton McHenry; Aaron Saxton (J. Big Data, 2020)

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources. - Eliu A. Huerta; Zhizhen Zhao 001 (CoRR, 2021)

A FAIR and AI-ready Higgs Boson Decay Dataset. - Yifan Chen; Eliu A. Huerta; Javier M. Duarte; Philip C. Harris; Daniel S. Katz; Mark S. Neubauer; Daniel Diaz 003; Farouk Mokhtar; Raghav Kansal; Sang Eon Park; Volodymyr V. Kindratenko; Zhizhen Zhao 001; et al. (CoRR, 2021)

Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers. - Asad Khan; Eliu A. Huerta; Huihuo Zheng (CoRR, 2021)

AI and extreme scale computing to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers. - Asad Khan; Eliu A. Huerta (CoRR, 2021)

Interpreting a Machine Learning Model for Detecting Gravitational Waves. - Mohammadtaher Safarzadeh; Asad Khan; Eliu A. Huerta; Martin Wattenberg (CoRR, 2022)

Applications of physics informed neural operators. - Shawn Rosofsky; Eliu A. Huerta (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)

MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge. - Marlin B. Schäfer; Ondrej Zelenka; Alexander H. Nitz; He Wang 018; Shichao Wu; Zong-Kuan Guo; Zhoujian Cao; Zhixiang Ren; Paraskevi Nousi; Nikolaos Stergioulas; Panagiotis Iosif; Alexandra E. Koloniari; et al. (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)

End-to-end AI Framework for Hyperparameter Optimization, Model Training, and Interpretable Inference for Molecules and Crystals. - Hyun Park; Ruijie Zhu 004; Eliu A. Huerta; Santanu Chaudhuri; Emad Tajkhorshid; Donny Cooper (CoRR, 2022)

Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale. - Pranshu Chaturvedi; Asad Khan; Minyang Tian; Eliu A. Huerta; Huihuo Zheng (Frontiers Artif. Intell., 2022)

Statistically-informed deep learning for gravitational wave parameter estimation. - Hongyu Shen; Eliu A. Huerta; Eamonn O'Shea; Prayush Kumar; Zhizhen Zhao 001 (Mach. Learn. Sci. Technol., 2022)

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Trung-Hieu Hoang; Minseok Ryu; Eliu A. Huerta; Volodymyr V. Kindratenko; Jordan D. Fuhrman; Maryellen L. Giger; Ryan Chard; Kibaek Kim; Ravi K. Madduri (e-Science, 2023)

GHP-MOFassemble: Diffusion modeling, high throughput screening, and molecular dynamics for rational discovery of novel metal-organic frameworks for carbon capture at scale. - Hyun Park; Xiaoli Yan; Ruijie Zhu 004; Eliu A. Huerta; Santanu Chaudhuri; Donny Cooper; Ian T. Foster; Emad Tajkhorshid (CoRR, 2023)

Physics-inspired spatiotemporal-graph AI ensemble for gravitational wave detection. - Minyang Tian; Eliu A. Huerta; Huihuo Zheng (CoRR, 2023)

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics. - Hyun Park; Parth Patel; Roland Haas; Eliu A. Huerta (CoRR, 2023)

AI ensemble for signal detection of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers. - Minyang Tian; Eliu A. Huerta; Huihuo Zheng (CoRR, 2023)

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx. - Trung-Hieu Hoang; Jordan D. Fuhrman; Ravi K. Madduri; Miao Li; Pranshu Chaturvedi; Zilinghan Li; Kibaek Kim; Minseok Ryu; Ryan Chard; Eliu A. Huerta; Maryellen L. Giger (CoRR, 2023)

Magnetohydrodynamics with physics informed neural operators. - Shawn G. Rosofsky; Eliu A. Huerta (Mach. Learn. Sci. Technol., 2023)

FAIR AI models in high energy physics. - Javier M. Duarte; Haoyang Li; Avik Roy; Ruike Zhu; Eliu A. Huerta; Daniel Diaz 003; Philip C. Harris; Raghav Kansal; Daniel S. Katz; Ishaan H. Kavoori; Volodymyr V. Kindratenko; Farouk Mokhtar; et al. (Mach. Learn. Sci. Technol., 2023)

Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows. - Bogdan Nicolae; Justin M. Wozniak; Tekin Bicer; Hai Nguyen; Parth Patel; Haochen Pan; Amal Gueroudji; Maxime Gonthier; Valérie Hayot-Sasson; Eliu A. Huerta; Kyle Chard; Ryan Chard; et al. (e-Science, 2024)

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler. - Zilinghan Li; Pranshu Chaturvedi; Shilan He; Han Chen; Gagandeep Singh; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (ICLR, 2024)

SciCode: A Research Coding Benchmark Curated by Scientists. - Minyang Tian; Luyu Gao; Shizhuo Dylan Zhang; Xinan Chen; Cunwei Fan; Xuefei Guo; Roland Haas; Pan Ji; Kittithat Krongchon; Yao Li; Shengyan Liu; Di Luo; et al. (NeurIPS, 2024)

SciCode: A Research Coding Benchmark Curated by Scientists. - Minyang Tian; Luyu Gao; Shizhuo Dylan Zhang; Xinan Chen; Cunwei Fan; Xuefei Guo; Roland Haas; Pan Ji; Kittithat Krongchon; Yao Li; Shengyan Liu; Di Luo; et al. (CoRR, 2024)

AI-driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State. - Semih Kacmaz; Roland Haas; Eliu A. Huerta (CoRR, 2024)

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (Comput. Sci. Eng., 2024)

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)

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants. - Franck Cappello; Sandeep Madireddy; Robert Underwood; Neil Getty; Nicholas Lee-Ping Chia; Nesar Ramachandra; Josh Nguyen; Murat Keçeli; Tanwi Mallick; Zilinghan Li; Marieme Ngom; Chenhui Zhang; et al. (CoRR, 2025)

Resolving Turbulent Magnetohydrodynamics: A Hybrid Operator-Diffusion Framework. - Semih Kacmaz; Eliu A. Huerta; Roland Haas (CoRR, 2025)