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Asad Khan

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Toward A Reinforcement-Learning-Based System for Adjusting Medication to Minimize Speech Disfluency

Dec 12, 2023
Pavlos Constas, Vikram Rawal, Matthew Honorio Oliveira, Andreas Constas, Aditya Khan, Kaison Cheung, Najma Sultani, Carrie Chen, Micol Altomare, Michael Akzam, Jiacheng Chen, Vhea He, Lauren Altomare, Heraa Murqi, Asad Khan, Nimit Amikumar Bhanshali, Youssef Rachad, Michael Guerzhoy

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Interpreting a Machine Learning Model for Detecting Gravitational Waves

Feb 15, 2022
Mohammadtaher Safarzadeh, Asad Khan, E. A. Huerta, Martin Wattenberg

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Inference-optimized AI and high performance computing for gravitational wave detection at scale

Jan 26, 2022
Pranshu Chaturvedi, Asad Khan, Minyang Tian, E. A. Huerta, Huihuo Zheng

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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

Dec 13, 2021
Asad Khan, E. A. Huerta

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Interpretable AI forecasting for numerical relativity waveforms of quasi-circular, spinning, non-precessing binary black hole mergers

Oct 13, 2021
Asad Khan, E. A. Huerta, Huihuo Zheng

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Confluence of Artificial Intelligence and High Performance Computing for Accelerated, Scalable and Reproducible Gravitational Wave Detection

Dec 15, 2020
E. A. Huerta, Asad Khan, Xiaobo Huang, Minyang Tian, Maksim Levental, Ryan Chard, Wei Wei, Maeve Heflin, Daniel S. Katz, Volodymyr Kindratenko, Dawei Mu, Ben Blaiszik, Ian Foster

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Physics-inspired deep learning to characterize the signal manifold of quasi-circular, spinning, non-precessing binary black hole mergers

Apr 20, 2020
Asad Khan, E. A. Huerta, Arnav Das

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Convergence of Artificial Intelligence and High Performance Computing on NSF-supported Cyberinfrastructure

Mar 18, 2020
E. A. Huerta, Asad Khan, Edward Davis, Colleen Bushell, William D. Gropp, Daniel S. Katz, Volodymyr Kindratenko, Seid Koric, William T. C. Kramer, Brendan McGinty, Kenton McHenry, Aaron Saxton

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Enabling real-time multi-messenger astrophysics discoveries with deep learning

Nov 26, 2019
E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

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Robotic Hierarchical Graph Neurons. A novel implementation of HGN for swarm robotic behaviour control

Oct 28, 2019
Phillip Smith, Aldeida Aleti, Vincent C. S. Lee, Robert Hunjet, Asad Khan

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