Arvind Ramanathan

99 papers A* 4A 3B 2C 3Misc 1Journal 56Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PRISM: Protocol Refinement through Intelligent Simulation Modeling. CoRR Brian Hsu, Priyanka Setty, Rory Butler, Ryan Lewis, Casey Stone, Rebecca Weinberg, Thomas S. Brettin, Rick L. Stevens, Ian T. Foster, Arvind Ramanathan
2025	J	`jnl`	A text-guided protein design framework. Nat. Mac. Intell. Shengchao Liu, Yanjing Li, Zhuoxinran Li, Anthony Gitter, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Arvind Ramanathan, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar
2025	J	`jnl`	ACE-RLHF: Automated Code Evaluation and Socratic Feedback Generation Tool using Large Language Models and Reinforcement Learning with Human Feedback. CoRR Tasnia Rahman, Sathish A. P. Kumar, Sumit Kumar Jha, Arvind Ramanathan
2025	—	`conf`	AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine. MLSys Carlo Siebenschuh, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Arham Mushtaq Khan, Khalid Hossain, Yadu N. Babuji, Nicholas Chia, Venkatram Vishwanath, Arvind Ramanathan, Rick L. Stevens, Ian T. Foster, Robert Underwood
2025	J	`jnl`	AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine. CoRR Carlo Siebenschuh, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Arham Khan, Khalid Hossain, Yadu N. Babuji, Nicholas Chia, Venkatram Vishwanath, Rick Stevens, Arvind Ramanathan, Ian T. Foster, Robert Underwood
2025	C	`conf`	Attr-RAG: Attribution-Guided Retrieval-Augmented Generation for Scientific Experiment Design. ICMLA Fazle Rahat, M. Shifat Hossain, Arvind Ramanathan, Sumit Kumar Jha, Hao Zheng, Rickard Ewetz
2025	—	`conf`	Automated MCQA Benchmarking at Scale: Evaluating Reasoning Traces as Retrieval Sources for Domain Adaptation of Small Language Models. SC Workshops Ozan Gökdemir, Neil Getty, Robert Underwood, Sandeep Madireddy, Franck Cappello, Arvind Ramanathan, Ian T. Foster, Rick L. Stevens
2025	J	`jnl`	Automated MCQA Benchmarking at Scale: Evaluating Reasoning Traces as Retrieval Sources for Domain Adaptation of Small Language Models. CoRR Ozan Gökdemir, Neil Getty, Robert Underwood, Sandeep Madireddy, Franck Cappello, Arvind Ramanathan, Ian T. Foster, Rick L. Stevens
2025	J	`jnl`	Connecting Large Language Model Agent to High Performance Computing Resource. CoRR Heng Ma, Alexander Brace, Carlo Siebenschuh, J. Gregory Pauloski, Ian T. Foster, Arvind Ramanathan
2025	J	`jnl`	DML-RAM: Deep Multimodal Learning Framework for Robotic Arm Manipulation using Pre-trained Models. CoRR Sathish Kumar, Swaroop Damodaran, Naveen Kumar Kuruba, Sumit Jha, Arvind Ramanathan
2025	J	`jnl`	Enhanced Penalty-based Bidirectional Reinforcement Learning Algorithms. CoRR Sai Gana Sandeep Pula, Sathish A. P. Kumar, Sumit Jha, Arvind Ramanathan
2025	J	`jnl`	Foundation Models for Discovery and Exploration in Chemical Space. CoRR Alexius Wadell, Anoushka Bhutani, Victor Azumah, Austin R. Ellis-Mohr, Celia Kelly, Hancheng Zhao, Anuj K. Nayak, Kareem Hegazy, Alexander Brace, Hongyi Lin, Murali Emani, Venkatram Vishwanath, Kevin Gering, Melisa Alkan, Tom Gibbs, Jack C. Wells, Lav R. Varshney, Bharath Ramsundar, Karthik Duraisamy, Michael W. Mahoney, Arvind Ramanathan, Venkatasubramanian Viswanathan
2025	—	`conf`	HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. PASC Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Setty, Aswathy Ajith, J. Gregory Pauloski, Varuni Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan
2025	J	`jnl`	HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. CoRR Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Vasanthakumari, Aswathy Ajith, J. Gregory Pauloski, Varuni Katti Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan
2025	—	`conf`	LangChain-Parsl: Connect Large Language Model Agents to High Performance Computing Resource. SC Workshops Heng Ma, Alexander Brace, Carlo Siebenschuh, Ian T. Foster, Arvind Ramanathan
2025	—	`conf`	MORAL: A Multimodal Reinforcement Learning Framework for Cognitive Intelligence in Autonomous Laboratories. CogMI Natalie Tirabassi, Sathish A. P. Kumar, Sumit Jha, Arvind Ramanathan
2025	J	`jnl`	MORAL: A Multimodal Reinforcement Learning Framework for Decision Making in Autonomous Laboratories. CoRR Natalie Tirabassi, Sathish A. P. Kumar, Sumit Jha, Arvind Ramanathan
2025	J	`jnl`	Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins. CoRR Matthew Sinclair, Moeen Meigooni, Archit Vasan, Ozan Gökdemir, Xinran Lian, Heng Ma, Yadu N. Babuji, Alexander Brace, Khalid Hossain, Carlo Siebenschuh, Thomas S. Brettin, Kyle Chard, Christopher S. Henry, Venkatram Vishwanath, Rick L. Stevens, Ian T. Foster, Arvind Ramanathan
2025	J	`jnl`	Self Distillation Fine-Tuning of Protein Language Models Improves Versatility in Protein Design. CoRR Amin Tavakoli, Raswanth Murugan, Ozan Gökdemir, Arvind Ramanathan, Frances H. Arnold, Anima Anandkumar
2024	J	`jnl`	BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. CoRR Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa
2024	A*	`conf`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	J	`jnl`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	—	`conf`	High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. IPDPS (Workshops) Archit Vasan, Ozan Gökdemir, Alexander Brace, Arvind Ramanathan, Thomas S. Brettin, Rick Stevens, Venkatram Vishwanath
2024	A	`conf`	MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. SC Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
2023	J	`jnl`	#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia A. Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro
2023	J	`jnl`	AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. J. Chem. Inf. Model. Rajendra P. Joshi, Katherine J. Schultz, Jesse William Wilson, Agustin Kruel, Rohith Anand Varikoti, Chathuri J. Kombala, Daniel W. Kneller, Stephanie Galanie, Gwyndalyn Phillips, Qiu Zhang, Leighton Coates, Jyothi Parvathareddy, Surekha Surendranathan, Ying Kong, Austin Clyde, Arvind Ramanathan, Colleen B. Jonsson, Kristoffer R. Brandvold, Mowei Zhou, Martha S. Head, Andrey Kovalevsky, Neeraj Kumar
2023	—	`conf`	Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. PASC Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens
2023	J	`jnl`	Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. CoRR Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens
2023	J	`jnl`	ChemoGraph: Interactive Visual Exploration of the Chemical Space. Comput. Graph. Forum Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, Michael E. Papka
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR 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 W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	J	`jnl`	GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 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 T. Ward, Valérie 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
2023	—	`conf`	Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. SC Workshops Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster
2023	J	`jnl`	Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. CoRR Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster
2023	J	`jnl`	Model certainty in cellular network-driven processes with missing data. PLoS Comput. Biol. Michael W. Irvin, Arvind Ramanathan, Carlos F. Lopez
2023	J	`jnl`	On the Robustness of AlphaFold: A COVID-19 Case Study. CoRR Ismail Alkhouri, Sumit Kumar Jha, Andre Beckus, George K. Atia, Alvaro Velasquez, Rickard Ewetz, Arvind Ramanathan, Susmit Jha
2023	—	`conf`	Protein Generation via Genome-scale Language Models with Bio-physical Scoring. SC Workshops Gautham Dharuman, Arvind Ramanathan
2023	—	`conf`	Scalable Lead Prediction with Transformers using HPC resources. SC Workshops Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath
2023	J	`jnl`	Towards a Modular Architecture for Science Factories. CoRR 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
2023	C	`conf`	Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. ICMLA Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Van Dam, Deyu Lu
2023	J	`jnl`	Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. CoRR Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Johannes Jacobus Van Dam, Deyu Lu
2022	A	`conf`	Coupling streaming AI and HPC ensembles to achieve 100-1000× faster biomolecular simulations. IPDPS Alexander Brace, Igor Yakushin, Heng Ma, Anda Trifan, Todd S. Munson, Ian T. Foster, Arvind Ramanathan, Hyungro Lee, Matteo Turilli, Shantenu Jha
2022	J	`jnl`	Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks. CoRR Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan
2022	J	`jnl`	High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. J. Chem. Inf. Model. 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
2022	J	`jnl`	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. 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
2022	A*	`conf`	Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. AAAI Sumit Kumar Jha, Rickard Ewetz, Alvaro Velasquez, Arvind Ramanathan, Susmit Jha
2021	J	`jnl`	AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. Int. J. High Perform. Comput. Appl. Lorenzo Casalino, Abigail C. Dommer, Zied Gaieb, Emília P. Barros, Terra Sztain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony T. Bogetti, Austin Clyde, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian T. Chong, Carlos Simmerling, David J. Hardy, Julio D. C. Maia, James C. Phillips, Thorsten Kurth, Abraham C. Stern, Lei Huang, John D. McCalpin, Mahidhar Tatineni, Tom Gibbs, John E. Stone, Shantenu Jha, Arvind Ramanathan, Rommie E. Amaro
2021	J	`jnl`	Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles. CoRR Alexander Brace, Hyungro Lee, Heng Ma, Anda Trifan, Matteo Turilli, Igor Yakushin, Todd S. Munson, Ian T. Foster, Shantenu Jha, Arvind Ramanathan
2021	—	`conf`	Adversarial Attacks against AI-driven Experimental Peptide Design Workflows. XLOOP@SC Arvind Ramanathan, Sumit Kumar Jha
2021	J	`jnl`	CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Models. CoRR Max Zvyagin, Thomas S. Brettin, Arvind Ramanathan, Sumit Kumar Jha
2021	J	`jnl`	Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites. J. Chem. Inf. Model. Eunice Cho, Margarida Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, Syed Tarique Moin, Mohammad Tanweer, Sarath Chandra Dantu, Alessandro Pandini, Junqi Yin, Heng Ma, Arvind Ramanathan, Barira Islam, Antonia S. J. S. Mey, Debsindhu Bhowmik, Shozeb M. Haider
2021	B	`conf`	IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP 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
2021	J	`jnl`	Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. CoRR 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
2021	J	`jnl`	Protein Folding Neural Networks Are Not Robust. CoRR Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz, Alvaro Velasquez, Susmit Jha
2021	J	`jnl`	Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening. CoRR 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
2021	—	`conf`	Prototypical Models for Classifying High-Risk Atypical Breast Lesions. MICCAI (8) Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Rebekah Jenkins, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla
2021	J	`jnl`	Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds. CoRR Austin Clyde, Arvind Ramanathan, Rick Stevens
2021	—	`conf`	Scalable HPC & AI infrastructure for COVID-19 therapeutics. PASC 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 R. Wilkinson, Shantenu Jha
2021	—	`conf`	Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. PASC Alexander Brace, Michael Salim, Vishal Subbiah, Heng Ma, Murali Emani, Anda Trifan, Austin R. Clyde, Corey Adams, Thomas D. Uram, Hyun Seung Yoo, Andew Hock, Jessica Liu, Venkatram Vishwanath, Arvind Ramanathan
2021	A*	`conf`	The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash
2021	J	`jnl`	Uncertainty-Informed Deep Transfer Learning of Perfluoroalkyl and Polyfluoroalkyl Substance Toxicity. J. Chem. Inf. Model. Jeremy Feinstein, Ganesh Sivaraman, Kurt Picel, Brian Peters, Álvaro Vázquez-Mayagoitia, Arvind Ramanathan, Margaret Macdonell, Ian T. Foster, Eugene Yan
2020	J	`jnl`	Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins. CoRR Arvind Ramanathan, Heng Ma, Akash Parvatikar, S. Chakra Chennubhotla
2020	J	`jnl`	Attacking NIST biometric image software using nonlinear optimization. Pattern Recognit. Lett. Sunny Raj, Jodh S. Pannu, Steven Lawrence Fernandes, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha
2020	J	`jnl`	Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan
2020	J	`jnl`	IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR 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
2020	—	`conf`	Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions. MICCAI (5) Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla
2020	J	`jnl`	Scalable HPC and AI Infrastructure for COVID-19 Therapeutics. CoRR 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 R. Wilkinson, Shantenu Jha
2020	J	`jnl`	Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. Atanu Acharya, Rupesh Agarwal, Matthew B. Baker, Jérôme Baudry, Debsindhu Bhowmik, Swen Böhm, Kendall G. Byler, Sam Yen-Chi Chen, Leighton Coates, Connor J. Cooper, Omar Demerdash, Isabella Daidone, John D. Eblen, Sally R. Ellingson, Stefano Forli, Jens Glaser, James C. Gumbart, John Gunnels, Oscar R. Hernandez, Stephan Irle, Daniel W. Kneller, Andrey Kovalevsky, Jeffrey M. Larkin, Travis J. Lawrence, Scott LeGrand, Shih-Hsien Liu, Julie C. Mitchell, Gilchan Park, Jerry M. Parks, Anna Pavlova, Loukas Petridis, Duncan Poole, Line Pouchard, Arvind Ramanathan, David M. Rogers, Diogo Santos-Martins, Aaron Scheinberg, Ada Sedova, Yue Shen, Jeremy C. Smith, Micholas Dean Smith, Carlos Soto, Aristides Tsaris, Mathialakan Thavappiragasam, Andreas F. Tillack, Josh Vincent Vermaas, Van Quan Vuong, Junqi Yin, Shinjae Yoo, Mai Zahran, Laura Zanetti Polzi
2020	J	`jnl`	Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release. CoRR 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
2019	J	`jnl`	Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle, Noah Schaefferkoetter, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Lynne Penberthy, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi, Arvind Ramanathan
2019	J	`jnl`	Data-driven efficient network and surveillance-based immunization. Knowl. Inf. Syst. Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, B. Aditya Prakash
2019	—	`conf`	Deep Generative Model Driven Protein Folding Simulations. PARCO Heng Ma, Debsindhu Bhowmik, Hyungro Lee, Matteo Turilli, Michael T. Young, Shantenu Jha, Arvind Ramanathan
2019	—	`conf`	DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. DLS@SC Hyungro Lee, Matteo Turilli, Shantenu Jha, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan
2019	J	`jnl`	DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. CoRR Hyungro Lee, Heng Ma, Matteo Turilli, Debsindhu Bhowmik, Shantenu Jha, Arvind Ramanathan
2019	—	`conf`	Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. BHI Hong-Jun Yoon, John Gounley, Shang Gao, Mohammed M. Alawad, Arvind Ramanathan, Georgia D. Tourassi
2019	—	`conf`	Towards Native Execution of Deep Learning on a Leadership-Class HPC System. IPDPS Workshops Srikanth B. Yoginath, Md. Maksudul Alam, Arvind Ramanathan, Debsindhu Bhowmik, Nouamane Laanait, Kalyan S. Perumalla
2019	—	`conf`	Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations. IEEE BigData Junghoon Chae, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan, Chad A. Steed
2018	J	`jnl`	Deep clustering of protein folding simulations. BMC Bioinform. Debsindhu Bhowmik, Shang Gao, Michael T. Young, Arvind Ramanathan
2018	—	`conf`	Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. IWBI Hong-Jun Yoon, Arvind Ramanathan, Folami Alamudun, Georgia D. Tourassi
2018	—	`conf`	Hierarchical Convolutional Attention Networks for Text Classification. Rep4NLP@ACL Shang Gao, Arvind Ramanathan, Georgia D. Tourassi
2018	J	`jnl`	Hierarchical attention networks for information extraction from cancer pathology reports. J. Am. Medical Informatics Assoc. Shang Gao, Michael T. Young, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Georgia D. Tourassi, Arvind Ramanathan
2018	C	`conf`	HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan
2018	J	`jnl`	Scalable deep text comprehension for Cancer surveillance on high-performance computing. BMC Bioinform. John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, James Blair Christian, Arvind Ramanathan, Xiao-Cheng Wu, Paul A. Fearn, Georgia D. Tourassi
2017	—	`conf`	Adversarial attacks on computer vision algorithms using natural perturbations. IC3 Arvind Ramanathan, Laura L. Pullum, Zubir Husein, Sunny Raj, Neslisah Torosdagli, Sumanta N. Pattanaik, Sumit Kumar Jha
2017	A*	`conf`	Data-Driven Immunization. ICDM Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura L. Pullum, B. Aditya Prakash
2017	—	`conf`	Testing autonomous cyber-physical systems using fuzzing features from convolutional neural networks: work-in-progress. EMSOFT Companion Sunny Raj, Sumit Kumar Jha, Arvind Ramanathan, Laura L. Pullum
2016	J	`jnl`	Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models. Simul. Özgür Özmen, James J. Nutaro, Laura L. Pullum, Arvind Ramanathan
2016	—	`conf`	Constellation: A science graph network for scalable data and knowledge discovery in extreme-scale scientific collaborations. IEEE BigData Sudharshan S. Vazhkudai, John Harney, Raghul Gunasekaran, Dale Stansberry, Seung-Hwan Lim, Tom Barron, Andrew Nash, Arvind Ramanathan
2016	A	`conf`	Integrating symbolic and statistical methods for testing intelligent systems: Applications to machine learning and computer vision. DATE Arvind Ramanathan, Laura L. Pullum, Faraz Hussain, Dwaipayan Chakrabarty, Sumit Kumar Jha
2016	—	`conf`	Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. INNS Conference on Big Data Hong-Jun Yoon, Arvind Ramanathan, Georgia D. Tourassi
2015	—	`conf`	NoC Architectures as Enablers of Biological Discovery for Personalized and Precision Medicine. NOCS Paul Bogdan, Turbo Majumder, Arvind Ramanathan, Yuankun Xue
2015	J	`jnl`	ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics. BMC Bioinform. Arvind Ramanathan, Laura L. Pullum, Tanner C. Hobson, Chad A. Steed, Shannon P. Quinn, Chakra S. Chennubhotla, Silvia Valkova
2015	—	`conf`	Sequential pattern mining of electronic healthcare reimbursement claims: Experiences and challenges in uncovering how patients are treated by physicians. IEEE BigData Kunal Malhotra, Tanner C. Hobson, Silvia Valkova, Laura L. Pullum, Arvind Ramanathan
2014	—	`conf`	EpiSpec: A formal specification language for parameterized agent-based models against epidemiological ground truth. ICCABS Faraz Hussain, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha
2014	—	`conf`	Oak Ridge Biosurveillance Toolkit: Scalable machine learning for public health surveillance. ICCABS Laura L. Pullum, Arvind Ramanathan
2013	J	`jnl`	Performance modeling of microsecond scale biological molecular dynamics simulations on heterogeneous architectures. Concurr. Comput. Pract. Exp. Pratul K. Agarwal, Scott S. Hampton, Jeffrey D. Poznanovic, Arvind Ramanathan, Sadaf R. Alam, Paul S. Crozier
2012	Misc	`conf`	Quasi-Anharmonic Analysis Reveals Intermediate States in the Nuclear Co-Activator Receptor Binding Domain Ensemble. Pacific Symposium on Biocomputing Virginia M. Burger, Arvind Ramanathan, Andrej J. Savol, Christopher B. Stanley, Pratul K. Agarwal, Chakra S. Chennubhotla
2011	J	`jnl`	QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin. Bioinform. Andrej J. Savol, Virginia M. Burger, Pratul K. Agarwal, Arvind Ramanathan, Chakra S. Chennubhotla
2010	J	`jnl`	An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. J. Comput. Biol. Arvind Ramanathan, Pratul K. Agarwal, Maria G. Kurnikova, Christopher James Langmead
2009	B	`conf`	An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. RECOMB Arvind Ramanathan, Pratul K. Agarwal, Maria G. Kurnikova, Christopher James Langmead