Arvind Ramanathan

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 68

Top Topics

Severe Acute Respiratory Syndrome

Machine Learning And Computer Vision

Intrinsically Disordered

Top Venues

J. Chem. Inf. Model.

Int. J. High Perform. Comput. Appl.

Publications

Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
Equivariant Graph Neural Operator for Modeling 3D Dynamics. 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)
Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia 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 Miller, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro
#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. 37 (1) (2023)
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)
Michael W. Irvin, Arvind Ramanathan, Carlos F. Lopez
Model certainty in cellular network-driven processes with missing data. PLoS Comput. Biol. 19 (4) (2023)
Ashka Shah, Arvind Ramanathan, Valérie Hayot-Sasson, Rick Stevens
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery. PASC (2023)
Gautham Dharuman, Arvind Ramanathan
Protein Generation via Genome-scale Language Models with Bio-physical Scoring. 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)
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
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. ICMLA (2023)
Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. SC Workshops (2023)
Ismail Alkhouri, Sumit Kumar Jha, Andre Beckus, George Atia, Alvaro Velasquez, Rickard Ewetz, Arvind Ramanathan, Susmit Jha
On the Robustness of AlphaFold: A COVID-19 Case Study. 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)
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)
Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath
Scalable Lead Prediction with Transformers using HPC resources. SC Workshops (2023)
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
AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. J. Chem. Inf. Model. 63 (5) (2023)
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
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. CoRR (2023)
Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. CoRR (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)
Sumit Kumar Jha, Rickard Ewetz, Alvaro Velasquez, Arvind Ramanathan, Susmit Jha
Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. AAAI (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)
Alexander Brace, Igor Yakushin, Heng Ma, Anda Trifan, Todd S. Munson, Ian T. Foster, Arvind Ramanathan, Hyungro Lee, Matteo Turilli, Shantenu Jha
Coupling streaming AI and HPC ensembles to achieve 100-1000× faster biomolecular simulations. IPDPS (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)
Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks. CoRR (2022)
Alexander Brace, Hyungro Lee, Heng Ma, Anda Trifan, Matteo Turilli, Igor Yakushin, Todd S. Munson, Ian T. Foster, Shantenu Jha, Arvind Ramanathan
Achieving 100X faster simulations of complex biological phenomena by coupling ML to HPC ensembles. CoRR (2021)
Arvind Ramanathan, Sumit Kumar Jha
Adversarial Attacks against AI-driven Experimental Peptide Design Workflows. XLOOP@SC (2021)
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
Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. PASC (2021)
Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD (2021)
Austin Clyde, Arvind Ramanathan, Rick Stevens
Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds. CoRR (2021)
Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Rebekah Jenkins, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla
Prototypical Models for Classifying High-Risk Atypical Breast Lesions. MICCAI (8) (2021)
Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz, Alvaro Velasquez, Susmit Jha
Protein Folding Neural Networks Are Not Robust. 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)
Eunice Cho, Margarida Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, Syed T. Moin, Mohammad Tanweer, Sarath Dantu, Alessandro Pandini, Junqi Yin, Heng Ma, Arvind Ramanathan, Barira Islam, Antonia S. J. S. Mey, Debsindhu Bhowmik, Shozeb M. Haider
Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites. J. Chem. Inf. Model. 61 (6) (2021)
Jeremy Feinstein, Ganesh Sivaraman, Kurt Picel, Brian Peters, Álvaro Vázquez-Mayagoitia, Arvind Ramanathan, Margaret Macdonell, Ian T. Foster, Eugene Yan
Uncertainty-Informed Deep Transfer Learning of Perfluoroalkyl and Polyfluoroalkyl Substance Toxicity. J. Chem. Inf. Model. 61 (12) (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)
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
AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. Int. J. High Perform. Comput. Appl. 35 (5) (2021)
Max Zvyagin, Thomas S. Brettin, Arvind Ramanathan, Sumit Kumar Jha
CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Models. 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)
Sunny Raj, Jodh S. Pannu, Steven Lawrence Fernandes, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha
Attacking NIST biometric image software using nonlinear optimization. Pattern Recognit. Lett. 131 (2020)
Arvind Ramanathan, Heng Ma, Akash Parvatikar, S. Chakra Chennubhotla
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins. CoRR (2020)
Akash Parvatikar, Om Choudhary, Arvind Ramanathan, Olga Navolotskaia, Gloria Carter, Akif Burak Tosun, Jeffrey L. Fine, S. Chakra Chennubhotla
Modeling Histological Patterns for Differential Diagnosis of Atypical Breast Lesions. MICCAI (5) (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)
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, D. W. Kneller, A. 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, Y. 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
Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. 60 (12) (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)
M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan
Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. 139 (2020)
Hong-Jun Yoon, John Gounley, Shang Gao, Mohammed M. Alawad, Arvind Ramanathan, Georgia D. Tourassi
Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. BHI (2019)
Hyungro Lee, Heng Ma, Matteo Turilli, Debsindhu Bhowmik, Shantenu Jha, Arvind Ramanathan
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. CoRR (2019)
Hyungro Lee, Matteo Turilli, Shantenu Jha, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding. DLS@SC (2019)
Srikanth B. Yoginath, Md. Maksudul Alam, Arvind Ramanathan, Debsindhu Bhowmik, Nouamane Laanait, Kalyan S. Perumalla
Towards Native Execution of Deep Learning on a Leadership-Class HPC System. IPDPS Workshops (2019)
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
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019)
Junghoon Chae, Debsindhu Bhowmik, Heng Ma, Arvind Ramanathan, Chad A. Steed
Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations. IEEE BigData (2019)
Heng Ma, Debsindhu Bhowmik, Hyungro Lee, Matteo Turilli, Michael T. Young, Shantenu Jha, Arvind Ramanathan
Deep Generative Model Driven Protein Folding Simulations. PARCO (2019)
Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, B. Aditya Prakash
Data-driven efficient network and surveillance-based immunization. Knowl. Inf. Syst. 61 (3) (2019)
Debsindhu Bhowmik, Shang Gao, Michael T. Young, Arvind Ramanathan
Deep clustering of protein folding simulations. BMC Bioinform. (18) (2018)
Shang Gao, Michael T. Young, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Georgia D. Tourassi, Arvind Ramanathan
Hierarchical attention networks for information extraction from cancer pathology reports. J. Am. Medical Informatics Assoc. 25 (3) (2018)
Shang Gao, Arvind Ramanathan, Georgia D. Tourassi
Hierarchical Convolutional Attention Networks for Text Classification. Rep4NLP@ACL (2018)
Hong-Jun Yoon, Arvind Ramanathan, Folami Alamudun, Georgia D. Tourassi
Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. IWBI (2018)
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
Scalable deep text comprehension for Cancer surveillance on high-performance computing. BMC Bioinform. (18) (2018)
M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan
HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD (2018)
Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura L. Pullum, B. Aditya Prakash
Data-Driven Immunization. ICDM (2017)
Sunny Raj, Laura Pullum, Arvind Ramanathan, Sumit Kumar Jha
: Defending Against Adversarial Attacks Using Statistical Hypothesis Testing. FPS (2017)
Arvind Ramanathan, Laura L. Pullum, Zubir Husein, Sunny Raj, Neslisah Torosdagli, Sumanta N. Pattanaik, Sumit Kumar Jha
Adversarial attacks on computer vision algorithms using natural perturbations. IC3 (2017)
Sunny Raj, Sumit Kumar Jha, Arvind Ramanathan, Laura L. Pullum
Testing autonomous cyber-physical systems using fuzzing features from convolutional neural networks: work-in-progress. EMSOFT Companion (2017)
Sudharshan S. Vazhkudai, John Harney, Raghul Gunasekaran, Dale Stansberry, Seung-Hwan Lim, Tom Barron, Andrew Nash, Arvind Ramanathan
Constellation: A science graph network for scalable data and knowledge discovery in extreme-scale scientific collaborations. IEEE BigData (2016)
Hong-Jun Yoon, Arvind Ramanathan, Georgia D. Tourassi
Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. INNS Conference on Big Data (2016)
Özgür Özmen, James J. Nutaro, Laura L. Pullum, Arvind Ramanathan
Analyzing the impact of modeling choices and assumptions in compartmental epidemiological models. Simul. 92 (5) (2016)
Arvind Ramanathan, Laura L. Pullum, Faraz Hussain, Dwaipayan Chakrabarty, Sumit Kumar Jha
Integrating symbolic and statistical methods for testing intelligent systems: Applications to machine learning and computer vision. DATE (2016)
Arvind Ramanathan, Laura L. Pullum, Tanner C. Hobson, Chad A. Steed, Shannon P. Quinn, Chakra S. Chennubhotla, Silvia Valkova
ORBiT: Oak Ridge biosurveillance toolkit for public health dynamics. BMC Bioinform. 16 (S17) (2015)
Kunal Malhotra, Tanner C. Hobson, Silvia Valkova, Laura L. Pullum, Arvind Ramanathan
Sequential pattern mining of electronic healthcare reimbursement claims: Experiences and challenges in uncovering how patients are treated by physicians. IEEE BigData (2015)
Paul Bogdan, Turbo Majumder, Arvind Ramanathan, Yuankun Xue
NoC Architectures as Enablers of Biological Discovery for Personalized and Precision Medicine. NOCS (2015)
Laura L. Pullum, Arvind Ramanathan
Oak Ridge Biosurveillance Toolkit: Scalable machine learning for public health surveillance. ICCABS (2014)
Faraz Hussain, Arvind Ramanathan, Laura L. Pullum, Sumit Kumar Jha
EpiSpec: A formal specification language for parameterized agent-based models against epidemiological ground truth. ICCABS (2014)
Pratul K. Agarwal, Scott S. Hampton, Jeffrey D. Poznanovic, Arvind Ramanathan, Sadaf R. Alam, Paul S. Crozier
Performance modeling of microsecond scale biological molecular dynamics simulations on heterogeneous architectures. Concurr. Comput. Pract. Exp. 25 (10) (2013)
Virginia M. Burger, Arvind Ramanathan, Andrej J. Savol, Christopher B. Stanley, Pratul K. Agarwal, Chakra Chennubhotla
Quasi-Anharmonic Analysis Reveals Intermediate States in the Nuclear Co-Activator Receptor Binding Domain Ensemble. Pacific Symposium on Biocomputing (2012)
Andrej J. Savol, Virginia M. Burger, Pratul K. Agarwal, Arvind Ramanathan, Chakra Chennubhotla
QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin. Bioinform. 27 (13) (2011)
Arvind Ramanathan, Pratul K. Agarwal, Maria Kurnikova, Christopher James Langmead
An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. J. Comput. Biol. 17 (3) (2010)
Arvind Ramanathan, Pratul K. Agarwal, Maria Kurnikova, Christopher James Langmead
An Online Approach for Mining Collective Behaviors from Molecular Dynamics Simulations. RECOMB (2009)