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Fingerprint Dive into the research topics where Shantenu Jha is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Molecular dynamics Engineering & Materials Science
Distributed computer systems Engineering & Materials Science
Middleware Engineering & Materials Science
Free energy Engineering & Materials Science
Interoperability Engineering & Materials Science
Computer simulation Engineering & Materials Science
Application programming interfaces (API) Engineering & Materials Science
Infrastructure Mathematics

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Projects 2012 2020

Research Output 2003 2019

CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space

Shkurti, A., Styliari, I. D., Balasubramanian, V., Bethune, I., Pedebos, C., Jha, S. & Laughton, C. A., Apr 9 2019, In : Journal of Chemical Theory and Computation. 15, 4, p. 2587-2596 10 p.

Rutgers, The State University

Research output: Contribution to journalArticle

sampling
Sampling
Principal component analysis
principal components analysis
Maltose-Binding Proteins

Computational reproducibility of scientific workflows at extreme scales

Pouchard, L., Baldwin, S., Elsethagen, T., Jha, S., Raju, B., Stephan, E., Tang, L. & Van Dam, K. K., Jan 1 2019, In : International Journal of High Performance Computing Applications.

Rutgers, The State University

Research output: Contribution to journalArticle

Scientific Workflow
Provenance
Reproducibility
Hybrid systems
Molecular dynamics

Incorporating Scientific Workflows in Computing Research Processes

Jha, S., Lathrop, S., Nabrzyski, J. & Ramakrishnan, L., Jul 1 2019, In : Computing in Science and Engineering. 21, 4, p. 4-6 3 p., 8744422.

Rutgers, The State University

Research output: Contribution to journalReview article

Learning everywhere: Pervasive machine learning for effective high-performance computation

Fox, G., Glazier, J., Kadupitiya, J. C. S., Jadhao, V., Kim, M., Qiu, J., Sluka, J. P., Somogy, E., Marathe, M., Adiga, A., Chen, J., Beckstein, O. & Jha, S., May 1 2019, Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019. Institute of Electrical and Electronics Engineers Inc., p. 422-429 8 p. 8778333. (Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019).

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning systems
Machine Learning
High Performance
Paradigm
Series

Middleware Building Blocks for Workflow Systems

Turilli, M., Balasubramanian, V., Merzky, A., Paraskevakos, I. & Jha, S., Jul 1 2019, In : Computing in Science and Engineering. 21, 4, p. 62-75 14 p., 8726147.

Rutgers, The State University

Research output: Contribution to journalArticle

Middleware