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Rick Stevens

Computing, Environment and Life Sciences, Argonne National Laboratory, Lemont, IL, USA, Department of Computer Science, The University of Chicago, Chicago, IL, USA

Learning from learning machines: a new generation of AI technology to meet the needs of science


Nov 27, 2021
Luca Pion-Tonachini, Kristofer Bouchard, Hector Garcia Martin, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus Zwart, Neeraj Kumar, Amy Justice, Claire Tomlin, Daniel Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Ken Kreutz-Delgado, Michael W. Mahoney, James B. Brown

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Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening


Jun 30, 2021
Austin Clyde, Thomas Brettin, Alexander Partin, Hyunseung Yoo, Yadu Babuji, Ben Blaiszik, Andre Merzky, Matteo Turilli, Shantenu Jha, Arvind Ramanathan, Rick Stevens

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Neko: a Library for Exploring Neuromorphic Learning Rules


May 01, 2021
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia

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Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds


Mar 11, 2021
Austin Clyde, Arvind Ramanathan, Rick Stevens

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Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers


Mar 04, 2021
Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, Andre Merzky, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney

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Learning Curves for Drug Response Prediction in Cancer Cell Lines


Nov 25, 2020
Alexander Partin, Thomas Brettin, Yvonne A. Evrard, Yitan Zhu, Hyunseung Yoo, Fangfang Xia, Songhao Jiang, Austin Clyde, Maulik Shukla, Michael Fonstein, James H. Doroshow, Rick Stevens

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* 14 pages, 7 figures 
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Regression Enrichment Surfaces: a Simple Analysis Technique for Virtual Drug Screening Models


Jun 01, 2020
Austin Clyde, Xiaotian Duan, Rick Stevens

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Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release


May 28, 2020
Yadu Babuji, Ben Blaiszik, Tom Brettin, Kyle Chard, Ryan Chard, Austin Clyde, Ian Foster, Zhi Hong, Shantenu Jha, Zhuozhao Li, Xuefeng Liu, Arvind Ramanathan, Yi Ren, Nicholaus Saint, Marcus Schwarting, Rick Stevens, Hubertus van Dam, Rick Wagner

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* 11 pages, 5 figures 
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Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response


May 13, 2020
Yitan Zhu, Thomas Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Hyunseung Yoo, James H. Doroshow, Rick Stevens

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Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing


May 11, 2020
Neil Getty, Thomas Brettin, Dong Jin, Rick Stevens, Fangfang Xia

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* 8 pages, 7 figures 
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A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning


May 04, 2020
Austin Clyde, Tom Brettin, Alexander Partin, Maulik Shaulik, Hyunseung Yoo, Yvonne Evrard, Yitan Zhu, Fangfang Xia, Rick Stevens

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Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research


Sep 01, 2019
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens

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* SC '19: IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis, November 17--22, 2019, Denver, CO 
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Precision Medicine as an Accelerator for Next Generation Cognitive Supercomputing


Apr 29, 2018
Edmon Begoli, Jim Brase, Bambi DeLaRosa, Penelope Jones, Dimitri Kusnezov, Jason Paragas, Rick Stevens, Fred Streitz, Georgia Tourassi

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* SUPERCOMPUTING FRONTIERS AND INNOVATIONS, 2018 
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Machine Learning for Antimicrobial Resistance


Jul 05, 2016
John W. Santerre, James J. Davis, Fangfang Xia, Rick Stevens

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* presented at 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications, New York, NY 
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