Rick Stevens

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 49

Top Topics

Virtual Screening

Neural Architecture

Severe Acute Respiratory Syndrome

Top Venues

Briefings Bioinform.

Nucleic Acids Res.

Publications

Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew R. Walter, Yuxin Chen
Blending Imitation and Reinforcement Learning for Robust Policy Improvement. ICLR (2024)
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. CoRR (2024)
Archit Vasan, Ozan Gökdemir, Alexander Brace, Arvind Ramanathan, Thomas S. Brettin, Rick Stevens, Venkatram Vishwanath
High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. IPDPS (Workshops) (2024)
Ashka Shah, Adela DePavia, Nathaniel Hudson, Ian T. Foster, Rick Stevens
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning. CoRR (2024)
Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, Michael E. Papka
ChemoGraph: Interactive Visual Exploration of the Chemical Space. Comput. Graph. Forum 42 (3) (2023)
Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. PASC (2023)
Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. NeurIPS (2023)
Oleksandr Narykov, Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Maulik Shukla, Priyanka Vasanthakumari, James H. Doroshow, Rick Stevens
Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction. SC Workshops (2023)
Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. CoRR (2023)
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37 (6) (2023)
Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. CoRR (2023)
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. BDCAT (2023)
Rafael Vescovi, Tobias Ginsburg, Kyle Hippe, Doga Ozgulbas, Casey Stone, Abraham Stroka, Rory Butler, Ben Blaiszik, Tom Brettin, Kyle Chard, Mark Hereld, Arvind Ramanathan, Rick Stevens, Aikaterini Vriza, Jie Xu, Qingteng Zhang, Ian T. Foster
Towards a Modular Architecture for Science Factories. CoRR (2023)
Justin M. Wozniak, Rajeev Jain, Andreas Wilke, Rylie Weaver, Alexander Partin, Thomas S. Brettin, Rick Stevens
An Automation Framework for Comparison of Cancer Response Models Across Configurations. e-Science (2023)
Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath
Scalable Lead Prediction with Transformers using HPC resources. SC Workshops (2023)
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR (2023)
Fangfang Xia, Jonathan E. Allen, Prasanna Balaprakash, Thomas S. Brettin, Cristina Garcia-Cardona, Austin Clyde, Judith D. Cohn, James H. Doroshow, Xiaotian Duan, Veronika Dubinkina, Yvonne A. Evrard, Ya Ju Fan, Jason Gans, Stewart He, Pinyi Lu, Sergei Maslov, Alexander Partin, Maulik Shukla, Eric A. Stahlberg, Justin M. Wozniak, Hyun Seung Yoo, George F. Zaki, Yitan Zhu, Rick Stevens
A cross-study analysis of drug response prediction in cancer cell lines. Briefings Bioinform. 23 (1) (2022)
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, Darin Hauner, Vilmos Kertesz, Neeraj Kumar, Hyungro Lee, Zhuozhao Li, André Merzky, Jurgen G. Schmidt, Li Tan, Mikhail Titov, Anda Trifan, Matteo Turilli, Hubertus Van Dam, Srinivas C. Chennubhotla, Shantenu Jha, Andrey Kovalevsky, Arvind Ramanathan, Martha S. Head, Rick Stevens
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. J. Chem. Inf. Model. 62 (1) (2022)
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, John D. McCalpin, Murali Emani, Hyenseung Yoo, Junqi Yin, Aristeidis Tsaris, Vishal Subbiah, Tanveer Raza, Jessica Liu, Noah Trebesch, Geoffrey Wells, Venkatesh Mysore, Tom Gibbs, James C. Phillips, S. Chakra Chennubhotla, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, John E. Stone, Emad Tajkhorshid, Sarah A Harris, Arvind Ramanathan
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. Int. J. High Perform. Comput. Appl. 36 (5-6) (2022)
Zachary S. Wallace, James J. Davis, Anna Maria Niewiadomska, Robert D. Olson, Maulik Shukla, Rick Stevens, Yun Zhang, Christian M. Zmasek, Richard H. Scheuermann
Early detection of emerging SARS-CoV-2 variants of interest for experimental evaluation. Frontiers Bioinform. 2 (2022)
Margo VanOeffelen, Marcus Nguyen, Derya Aytan-Aktug, Thomas S. Brettin, Emily M. Dietrich, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Robert Olson, Gordon D. Pusch, Maulik Shukla, Rick Stevens, Veronika Vonstein, Andrew S. Warren, Alice R. Wattam, Hyun Seung Yoo, James J. Davis
A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes. Briefings Bioinform. 22 (6) (2021)
Luca Pion-Tonachini, Kristofer E. Bouchard, Héctor García Martín, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko M. Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown
Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR (2021)
Austin Clyde, Arvind Ramanathan, Rick Stevens
Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds. CoRR (2021)
Hyungro Lee, André Merzky, Li Tan, Mikhail Titov, Matteo Turilli, Dario Alfè, Agastya Bhati, Alex Brace, Austin Clyde, Peter V. Coveney, Heng Ma, Arvind Ramanathan, Rick Stevens, Anda Trifan, Hubertus Van Dam, Shunzhou Wan, Sean Wilkinson, Shantenu Jha
Scalable HPC & AI infrastructure for COVID-19 therapeutics. PASC (2021)
Romain Égelé, Prasanna Balaprakash, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu
AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. SC (2021)
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
Neko: a Library for Exploring Neuromorphic Learning Rules. ICONS (2021)
Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, André 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
Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. CoRR (2021)
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
Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. CoRR (2021)
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
Neko: a Library for Exploring Neuromorphic Learning Rules. CoRR (2021)
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, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Dieter Kranzlmüller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, André Merzky, Alexander Partin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Anda Trifan, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling, Junqi Yin
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP (2021)
Murali Emani, Venkatram Vishwanath, Corey Adams, Michael E. Papka, Rick Stevens, Laura Florescu, Sumti Jairath, William Liu, Tejas Nama, Arvind Sujeeth, Volodymyr V. Kindratenko, Anne C. Elster
Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture. Comput. Sci. Eng. 23 (2) (2021)
Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Hyun Seung Yoo, James H. Doroshow, Rick Stevens
Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response. CoRR (2020)
Alexander Partin, Thomas S. Brettin, Yvonne A. Evrard, Yitan Zhu, Hyun Seung Yoo, Fangfang Xia, Songhao Jiang, Austin Clyde, Maulik Shukla, Michael Fonstein, James H. Doroshow, Rick Stevens
Learning Curves for Drug Response Prediction in Cancer Cell Lines. CoRR (2020)
James J. Davis, Alice R. Wattam, Ramy K. Aziz, Thomas S. Brettin, Ralph Butler, Rory Butler, Philippe Chlenski, Neal Conrad, Allan Dickerman, Emily M. Dietrich, Joseph L. Gabbard, Svetlana Gerdes, Andrew Guard, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Daniel E. Murphy-Olson, Marcus Nguyen, Eric K. Nordberg, Gary J. Olsen, Robert Olson, Jamie C. Overbeek, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, Maulik Shukla, Chris Thomas, Margo VanOeffelen, Veronika Vonstein, Andrew S. Warren, Fangfang Xia, Dawen Xie, Hyun Seung Yoo, Rick Stevens
The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities. Nucleic Acids Res. 48 (Database-Issue) (2020)
Austin Clyde, Tom Brettin, Alexander Partin, Maulik Shaulik, Hyun Seung Yoo, Yvonne A. Evrard, Yitan Zhu, Fangfang Xia, Rick Stevens
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning. CoRR (2020)
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, Yi Ren, Nicholaus Saint, Marcus Schwarting, Rick Stevens, Hubertus Van Dam, Rick Wagner
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. CoRR (2020)
Hyungro Lee, André Merzky, Li Tan, Mikhail Titov, Matteo Turilli, Dario Alfè, Agastya Bhati, Alex Brace, Austin Clyde, Peter V. Coveney, Heng Ma, Arvind Ramanathan, Rick Stevens, Anda Trifan, Hubertus Van Dam, Shunzhou Wan, Sean Wilkinson, Shantenu Jha
Scalable HPC and AI Infrastructure for COVID-19 Therapeutics. CoRR (2020)
Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Thomas S. Brettin, Kyle Chard, Ryan Chard, Peter V. Coveney, Anda Trifan, Alex Brace, Austin Clyde, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Thorsten Kurth, Dieter Kranzlmüller, Hyungro Lee, Zhuozhao Li, Heng Ma, André Merzky, Gerald Mathias, Alexander Partin, Junqi Yin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR (2020)
Rick Stevens
Overview of HPC and AI Computing for COVID-19 in the US. PACT (2020)
Neil Getty, Thomas S. Brettin, Dong Jin, Rick Stevens, Fangfang Xia
Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing. CoRR (2020)
Justin M. Wozniak, Hyun Seung Yoo, Jamaludin Mohd-Yusof, Bogdan Nicolae, Nicholson T. Collier, Jonathan Ozik, Thomas S. Brettin, Rick Stevens
High-bypass Learning: Automated Detection of Tumor Cells That Significantly Impact Drug Response. MLHPC/AI4S@SC (2020)
Austin Clyde, Xiaotian Duan, Rick Stevens
Regression Enrichment Surfaces: a Simple Analysis Technique for Virtual Drug Screening Models. CoRR (2020)
Xingfu Wu, Valerie E. Taylor, Justin M. Wozniak, Rick Stevens, Thomas S. Brettin, Fangfang Xia
Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks. ICPP (2019)
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. SC (2019)
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. CoRR (2019)
Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson T. Collier, John Bauer, Fangfang Xia, Thomas S. Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia-Cardona, Brian Van Essen, Matthew Baughman
CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research. BMC Bioinform. (18) (2018)
George F. Zaki, Justin M. Wozniak, Jonathan Ozik, Nicholson T. Collier, Thomas S. Brettin, Rick Stevens
Portable and Reusable Deep Learning Infrastructure with Containers to Accelerate Cancer Studies. ESPM2@SC (2018)
Edmon Begoli, Jim Brase, Bambi DeLaRosa, Penelope Jones, Dimitri Kusnezov, Jason Paragas, Rick Stevens, Fred Streitz, Georgia D. Tourassi
Precision Medicine as an Accelerator for Next Generation Cognitive Supercomputing. CoRR (2018)
Rick Stevens
Deep Learning in Cancer and Infectious Disease: Novel Driver Problems for Future HPC Architecture. HPDC (2017)
Ross A. Overbeek, Robert Olson, Gordon D. Pusch, Gary J. Olsen, James J. Davis, Terry Disz, Robert A. Edwards, Svetlana Gerdes, Bruce D. Parrello, Maulik Shukla, Veronika Vonstein, Alice R. Wattam, Fangfang Xia, Rick Stevens
The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 42 (Database-Issue) (2014)
Robert A. Edwards, Robert Olson, Terry Disz, Gordon D. Pusch, Veronika Vonstein, Rick Stevens, Ross A. Overbeek
-mers to annotate metagenomes. Bioinform. 28 (24) (2012)
Jack J. Dongarra, Peter H. Beckman, Terry Moore, Patrick Aerts, Giovanni Aloisio, Jean-Claude Andre, David Barkai, Jean-Yves Berthou, Taisuke Boku, Bertrand Braunschweig, Franck Cappello, Barbara M. Chapman, Xuebin Chi, Alok N. Choudhary, Sudip S. Dosanjh, Thom H. Dunning, Sandro Fiore, Al Geist, Bill Gropp, Robert J. Harrison, Mark Hereld, Michael A. Heroux, Adolfy Hoisie, Koh Hotta, Zhong Jin, Yutaka Ishikawa, Fred Johnson, Sanjay Kale, Richard Kenway, David E. Keyes, Bill Kramer, Jesús Labarta, Alain Lichnewsky, Thomas Lippert, Bob Lucas, Barney Maccabe, Satoshi Matsuoka, Paul Messina, Peter Michielse, Bernd Mohr, Matthias S. Müller, Wolfgang E. Nagel, Hiroshi Nakashima, Michael E. Papka, Daniel A. Reed, Mitsuhisa Sato, Edward Seidel, John Shalf, David Skinner, Marc Snir, Thomas L. Sterling, Rick Stevens, Fred Streitz, Bob Sugar, Shinji Sumimoto, William M. Tang, John Taylor, Rajeev Thakur, Anne E. Trefethen, Mateo Valero, Aad J. van der Steen, Jeffrey S. Vetter, Peg Williams, Robert W. Wisniewski, Katherine A. Yelick
The International Exascale Software Project roadmap. Int. J. High Perform. Comput. Appl. 25 (1) (2011)
Terry Disz, Sajia Akhter, Daniel Cuevas, Robert Olson, Ross A. Overbeek, Veronika Vonstein, Rick Stevens, Robert A. Edwards
Accessing the SEED genome databases via Web services API: tools for programmers. BMC Bioinform. 11 (2010)
Fangfang Xia, Rick Stevens
Inferring a Species Tree from Gene Trees in the Presence of HGT. BIOCOMP (2009)
Jack J. Dongarra, Peter H. Beckman, Patrick Aerts, Franck Cappello, Thomas Lippert, Satoshi Matsuoka, Paul Messina, Terry Moore, Rick Stevens, Anne E. Trefethen, Mateo Valero
The International Exascale Software Project: a Call To Cooperative Action By the Global High-Performance Community. Int. J. High Perform. Comput. Appl. 23 (4) (2009)
Florent E. Angly, Dana Willner, Alejandra Prieto-Davó, Robert A. Edwards, Robert Schmieder, Rebecca Vega-Thurber, Dionysios A. Antonopoulos, Katie Barott, Matthew T. Cottrell, Christelle Desnues, Elizabeth A. Dinsdale, Mike Furlan, Matthew Haynes, Matthew R. Henn, Yongfei Hu, David L. Kirchman, Tracey McDole, John D. McPherson, Folker Meyer, R. Michael Miller, Egbert Mundt, Robert K. Naviaux, Beltran Rodriguez-Mueller, Rick Stevens, Linda Wegley, Lixin Zhang, Baoli Zhu, Forest Rohwer
The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes. PLoS Comput. Biol. 5 (12) (2009)
Wim van Drongelen, Hyong Lee, Amber Martell, Jennifer Dwyer, Rick Stevens, Mark Hereld
Oscillation in a network model of neocortex. ESANN (2009)
Folker Meyer, Daniel Paarmann, Mark D'Souza, Robert Olson, Elizabeth M. Glass, Michael Kubal, Tobias Paczian, Alexis A. Rodriguez, Rick Stevens, Andreas Wilke, Jared Wilkening, Robert A. Edwards
The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinform. 9 (2008)
Jonathan C. Silverstein, Colin Walsh, Fred Dech, Eric C. Olson, Michael E. Papka, Nigel M. Parsad, Rick Stevens
Multi-Parallel Open Technology to Enable Collaborative Volume Visualization: How to Create Global Immersive Virtual Anatomy Classrooms. MMVR (2008)
Xinghua Shi, Rick Stevens
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models. CLADE (2008)
Guang R. Gao, Thomas L. Sterling, Rick Stevens, Mark Hereld, Weirong Zhu
ParalleX: A Study of A New Parallel Computation Model. IPDPS (2007)
Leslie Klis McNeil, Claudia Reich, Ramy K. Aziz, Daniela Bartels, Matthew Cohoon, Terry Disz, Robert A. Edwards, Svetlana Gerdes, Kaitlyn Hwang, Michael Kubal, Gohar Rem Margaryan, Folker Meyer, William Mihalo, Gary J. Olsen, Robert Olson, Andrei Osterman, Daniel Paarmann, Tobias Paczian, Bruce D. Parrello, Gordon D. Pusch, Dmitry A. Rodionov, Xinghua Shi, Olga Vassieva, Veronika Vonstein, Olga Zagnitko, Fangfang Xia, Jenifer Zinner, Ross A. Overbeek, Rick Stevens
The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation. Nucleic Acids Res. 35 (Database-Issue) (2007)
Aditi Majumder, Rick Stevens
Perceptual photometric seamlessness in projection-based tiled displays. ACM Trans. Graph. 24 (1) (2005)
Aditi Majumder, Rick Stevens
Color Nonuniformity in Projection-Based Displays: Analysis and Solutions. IEEE Trans. Vis. Comput. Graph. 10 (2) (2004)
Xingfu Wu, Jonathan Geisler, Rick Stevens
Isocoupling: Reusing Kernel Coupling Values to Predict the Performance of Parallel Applications. IPDPS (2004)
Aditi Majumder, Rick Stevens
LAM: luminance attenuation map for photometric uniformity in projection based displays. VRST (2002)
Guang R. Gao, Kevin B. Theobald, Ziang Hu, Haiping Wu, Jizhu Lu, Keshav Pingali, Paul Stodghill, Thomas L. Sterling, Rick Stevens, Mark Hereld
Next Generation System Software for Future High-End Computing Systems. IPDPS (2002)
Robert Rosner, Alan C. Calder, Jonathan Dursi, Bruce Fryxell, Donald Q. Lamb, Jens C. Niemeyer, Kevin Olson, Paul M. Ricker, Frank X. Timmes, James W. Truran, Henry M. Tufo, Yuan-Nan Young, Michael Zingale, Ewing L. Lusk, Rick Stevens
Flash code: studying astrophysical thermonuclear flashes. Comput. Sci. Eng. 2 (2) (2000)
Rick Stevens, Paul R. Woodward, Thomas A. DeFanti, Charles E. Catlett
From the I-WAY to the National Technology Grid. Commun. ACM 40 (11) (1997)
Valerie E. Taylor, Milana Huang, Thomas Canfield, Rick Stevens, Daniel A. Reed, Stephen E. Lamm
Performance Modeling of Interactive, Immersive Virtual Environments for Finite Element Simulations. Int. J. High Perform. Comput. Appl. 10 (2-3) (1996)
Robert J. Harrison, Martyn F. Guest, Ricky A. Kendall, David E. Bernholdt, Adrian T. Wong, Mark Stave, James L. Anchell, Anthony C. Hess, Rik J. Littlefield, George L. Fann, Jarek Nieplocha, Greg S. Thomas, David Elwood, Jeffrey L. Tilson, Ron L. Shepard, Albert F. Wagner, Ian T. Foster, Ewing L. Lusk, Rick Stevens
Toward high-performance computational chemistry: II. A scalable self-consistent field program. J. Comput. Chem. 17 (1) (1996)
Thomas A. DeFanti, Ian T. Foster, Michael E. Papka, Rick Stevens, Tim Kuhfuss
Overview of the I-Way: Wide-Area Visual Supercomputing. Int. J. High Perform. Comput. Appl. 10 (2-3) (1996)
Alok N. Choudhary, Ian T. Foster, Rick Stevens
Multimedia Applications and High-Performance Computing. IEEE Parallel Distributed Technol. Syst. Appl. 3 (2) (1995)
Terrence Disz, Rémy Evard, Mark Henderson, William Nickless, Robert Olson, Michael E. Papka, Rick Stevens
Designing the future of collaborative science: Argonne's Futures Laboratory. IEEE Parallel Distributed Technol. Syst. Appl. 3 (2) (1995)
Shirley Browne, Jack J. Dongarra, Geoffrey C. Fox, Kenneth A. Hawick, Ken Kennedy, Rick Stevens, Robert Olson, Tom Rowan
Distributed Information Management in the National HPCC Software Exchange. SC (1995)
Rick Stevens
Multimedia Supercomputing: The Use of Supercomputers to Drive High-Performance Multimedia Systems and Virtual Environments. HPDC (1994)
Rick Stevens
High-performance computing and communications. Future Gener. Comput. Syst. 10 (2-3) (1994)
Ewing L. Lusk, Ralph Butler, Terrence Disz, Robert Olson, Ross A. Overbeek, Rick Stevens, David H. D. Warren, Alan Calderwood, Péter Szeredi, Seif Haridi
The Aurora or-parallel Prolog system. New Gener. Comput. 7 (2-3) (1990)
Tie-Cheng Wang, Rick Stevens
Solving Open Problems in Right Alternative Rings with Z-Module Reasoning. J. Autom. Reason. 5 (2) (1989)