World's Best Scientists 2026 revealed!
Venkat Venkatasubramanian

Venkat Venkatasubramanian

D-Index & Metrics

Computer Science

D-Index
63
Citations
19927
World Ranking
2710
National Ranking
1347

Venkat Venkatasubramanian publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Venkat Venkatasubramanian sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 258 publications — 65th percentile

65% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Venkat Venkatasubramanian D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Venkat Venkatasubramanian sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 63 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Venkat Venkatasubramanian is affiliated with Columbia University in the United States and contributes extensively to the fields of engineering and computer science. Their research mainly focuses on control and systems engineering, artificial intelligence, statistical and nonlinear physics, molecular biology, and materials chemistry.

The scientist's work encompasses multiple topics, including:

  • Fault Detection and Control Systems
  • Machine Learning in Materials Science
  • Computational Drug Discovery Methods
  • Advanced Thermodynamics and Statistical Mechanics
  • Reservoir Engineering and Simulation Methods
  • Micro and Nano Robotics
  • Process Optimization and Integration

Venkat Venkatasubramanian has published research in a variety of venues, with notable frequent publication in:

  • Computers & Chemical Engineering
  • arXiv (Cornell University)
  • AIChE Journal
  • Current Opinion in Chemical Engineering
  • Fluid Phase Equilibria

Some of their recent papers include:

  • "Process systems engineering - The generation next?", 2021, Computers & Chemical Engineering
  • "Artificial intelligence in reaction prediction and chemical synthesis", 2021, Current Opinion in Chemical Engineering
  • "Predicting chemical reaction outcomes: A grammar ontology-based transformer framework", 2021, AIChE Journal
  • "Hidden representations in deep neural networks: Part 2. Regression problems", 2020, Computers & Chemical Engineering
  • "AI-DARWIN: A first principles-based model discovery engine using machine learning", 2021, Computers & Chemical Engineering

Many of their publications have involved collaborations with frequent co-authors such as Abhishek Sivaram, Vipul Mann, Arijit Chakraborty, Rafiqul Gani, and N. Sanjeevrajan. These collaborations have contributed significantly to the research output and development of various approaches in process systems engineering and artificial intelligence applications in chemical engineering.

Best Publications

  • A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods

    Venkat Venkatasubramanian;Raghunathan Rengaswamy;Kewen Yin;Surya N. Kavuri

  • A review of process fault detection and diagnosis: Part III: Process history based methods

    Venkat Venkatasubramanian;Raghunathan Rengaswamy;Surya N. Kavuri;Kewen Yin

  • A review of process fault detection and diagnosis Part II : Qualitative models and search strategies

    Venkat Venkatasubramanian;Raghunathan Rengaswamy;Surya N. Kavuri

  • The promise of artificial intelligence in chemical engineering: Is it here, finally?

    Venkat Venkatasubramanian

  • A neural network methodology for process fault diagnosis

    Venkat Venkatasubramanian;King Chan

  • Process fault detection and diagnosis using neural networks—I. steady-state processes

    V. Venkatasubramanian;R. Vaidyanathan;Y. Yamamoto

  • Sulfur Vulcanization of Natural Rubber for Benzothiazole Accelerated Formulations: From Reaction Mechanisms to a Rational Kinetic Model

    Prasenjeet Ghosh;Santhoji Katare;Priyan Patkar;James M. Caruthers

  • Computer-aided molecular design using genetic algorithms

    V. Venkatasubramanian;K. Chan;J.M. Caruthers

  • Challenges in the industrial applications of fault diagnostic systems

    Sourabh Dash;Venkat Venkatasubramanian

  • Intelligent systems for HAZOP analysis of complex process plants

    Venkat Venkatasubramanian;Jinsong Zhao;Shankar Viswanathan

  • Process systems engineering – The generation next?

    Efstratios N. Pistikopoulos;Ana Barbosa-Póvoa;Jay H. Lee;Ruth Misener

  • A syntactic pattern-recognition approach for process monitoring and fault diagnosis

    Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • PCA-SDG based process monitoring and fault diagnosis

    Hiranmayee Vedam;Venkat Venkatasubramanian

  • Automatic generation of qualitative descriptions of process trends for fault detection and diagnosis

    Margaret E. Janusz;Venkat Venkatasubramanian

  • Fault diagnosis using dynamic trend analysis: A review and recent developments

    Mano Ram Maurya;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • A genetic algorithmic framework for process design and optimization

    I.P. Androulakis;V. Venkatasubramanian

  • Model-based reasoning in diagnostic expert systems for chemical process plants

    Steven H. Rich;V. Venkatasubramanian

  • Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets

    Mano Ram Maurya;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • Fuzzy-logic based trend classification for fault diagnosis of chemical processes

    Sourabh Dash;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • Evolutionary Design of Molecules with Desired Properties Using the Genetic Algorithm

    Venkat Venkatasubramanian;King Chan;James M. Caruthers

  • A hybrid genetic algorithm for efficient parameter estimation of large kinetic models

    Santhoji Katare;Aditya Bhan;James M. Caruthers;W. Nicholas Delgass

Frequent Co-Authors

Raghunathan Rengaswamy
Raghunathan Rengaswamy Indian Institute of Technology Madras
Gintaras V. Reklaitis
Gintaras V. Reklaitis Purdue University West Lafayette
Rafiqul Gani
Rafiqul Gani Széchenyi István University
Rajagopalan Srinivasan
Rajagopalan Srinivasan Indian Institute of Technology Madras
Aditya Bhan
Aditya Bhan University of Minnesota
Francis J. Doyle
Francis J. Doyle Brown University
W. Nicholas Delgass
W. Nicholas Delgass Purdue University West Lafayette
Karl-Erik Årzén
Karl-Erik Årzén Lund University
Joseph F. Pekny
Joseph F. Pekny Purdue University West Lafayette
Sanat K. Kumar
Sanat K. Kumar Columbia University

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