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Venkat Venkatasubramanian

Venkat Venkatasubramanian

D-Index & Metrics

Computer Science

D-Index
63
Citations
19927
World Ranking
2710
National Ranking
1346

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
Francis J. Doyle
Francis J. Doyle Brown University
Karl-Erik Årzén
Karl-Erik Årzén Lund University
Sanat K. Kumar
Sanat K. Kumar Columbia University
Joseph F. Pekny
Joseph F. Pekny Purdue University West Lafayette
Shankar Narasimhan
Shankar Narasimhan Indian Institute of Technology Madras
Oleg Gang
Oleg Gang Columbia University

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