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Shantenu Jha

Data Driven Discovery High Performance Computing Scientific Workflow Management Computational Science
Rutgers University Department of Computer Science

About

Shantenu is a Professor of Computer Engineering at Rutgers University and the Chair of the Department (Center) for Data Driven Discovery at Brookhaven National Laboratory. He was appointed a Rutgers Chancellor’s Scholar in 2015. He has held visiting positions at the University of Edinburgh and UCL.

Research Performance Summary

359
Total Papers
6331
Total Citations
42
H-Index
1999-2026
Active Research Span

First Recorded Paper

LB3D V7

Year: 1999

Citations: 0

Venue: N/A

Latest Recorded Paper

A terminology for scientific workflow systems

Year: 2026

Citations: 20

Venue: Future Generation Computer Systems 174

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
1
2025
17
2024
28
2023
26
2022
11
2021
24
2020
8
2019
23
2018
28
2017
22
2016
18

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 138
Journal 32
Book 5

Top Coauthors

Jha Turilli

Research Impact by Period

2025-2026

Period Stats
Papers 18
Citations 108
Avg. Citations / Paper 6
H-Index 5

2020-2024

Period Stats
Papers 97
Citations 1907
Avg. Citations / Paper 19.7
H-Index 25

2015-2019

Period Stats
Papers 108
Citations 1791
Avg. Citations / Paper 16.6
H-Index 23

2010-2014

Period Stats
Papers 76
Citations 1302
Avg. Citations / Paper 17.1
H-Index 19

2005-2009

Period Stats
Papers 52
Citations 1008
Avg. Citations / Paper 19.4
H-Index 17

2000-2004

Period Stats
Papers 7
Citations 215
Avg. Citations / Paper 30.7
H-Index 5

1995-1999

Period Stats
Papers 1
Citations 0
Avg. Citations / Paper 0
H-Index 0

Contact and Professional Links

Contact Information

shantenu.jha@rutgers.edu
8484458537

Detected Research Keywords

Workflows Community Summit Replica Exchange Simulations Simple Api Grid Api Grid Applications Workload Management System Molecular Dynamics Simulations Ml Driven Hpc Heterogeneous Workloads Scale Binding Free Energies Framework Assessing Changes