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Engineering and Technology

D-Index
46
Citations
14861
World Ranking
5036
National Ranking
81

Overview

Raghunathan Rengaswamy is affiliated with the Indian Institute of Technology Madras in India. Their research primarily spans the field of Engineering, with a focus on several subfields including Molecular Biology, Electrical and Electronic Engineering, Biomedical Engineering, Control and Systems Engineering, and Artificial Intelligence.

The scientist's work covers a variety of topics such as Fault Detection and Control Systems, Innovative Microfluidic and Catalytic Techniques Innovation, Electrowetting and Microfluidic Technologies, Advanced Battery Technologies Research, Microfluidic and Capillary Electrophoresis Applications, Pregnancy and preeclampsia studies, and Machine Learning in Materials Science.

Rengaswamy has numerous publications distributed across several frequent venues. The venues with multiple contributions include Zenodo (CERN European Organization for Nuclear Research), arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), AIChE Journal, and Computers & Chemical Engineering.

Recent publications of note include:

  • Integration of machine learning and first principles models, 2022, AIChE Journal
  • Metabolic modeling of host-microbe interactions for therapeutics in colorectal cancer, 2022, npj Systems Biology and Applications
  • A Computational Framework for Studying Gut-Brain Axis in Autism Spectrum Disorder, 2022, Frontiers in Physiology
  • Novel ratio-metric features enable the identification of new driver genes across cancer types, 2022, Scientific Reports
  • Designing Biological Circuits: From Principles to Applications, 2022, ACS Synthetic Biology

Their research collaborations have been frequent with several coauthors including Malvika Sudhakar, Karthik Raman, Ramachandran Thiruvengadam, and Resmi Suresh.

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

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

    Raghunathan Rengaswamy;Venkat Venkatasubramanian

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

    Mano Ram Maurya;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • Locating sensors in complex chemical plants based on fault diagnostic observability criteria

    Rao Raghuraj;Mani Bhushan;Raghunathan Rengaswamy

  • Robust and reliable estimation via Unscented Recursive Nonlinear Dynamic Data Reconciliation

    Pramod Vachhani;Shankar Narasimhan;Raghunathan Rengaswamy

  • A Review of Solid Oxide Fuel Cell (SOFC) Dynamic Models

    Debangsu Bhattacharyya;Raghunathan Rengaswamy

  • 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

  • Control Loop Performance Assessment. 2. Hammerstein Model Approach for Stiction Diagnosis

    Ranganathan Srinivasan;Raghunathan Rengaswamy;Shankar Narasimhan;Randy Miller

  • A Systematic Framework for the Development and Analysis of Signed Digraphs for Chemical Processes. 1. Algorithms and Analysis

    Mano Ram Maurya;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • A qualitative shape analysis formalism for monitoring control loop performance

    R Rengaswamy;Tore Hägglund;V. Venkatasubramanian

  • Solid Oxide Fuel Cell Modeling

    A. Gebregergis;P. Pillay;D. Bhattacharyya;R. Rengaswemy

  • A Signed Directed Graph and Qualitative Trend Analysis-Based Framework for Incipient Fault Diagnosis

    M.R. Maurya;R. Rengaswamy;V. Venkatasubramanian

  • Recursive estimation in constrained nonlinear dynamical systems

    Pramod Vachhani;Raghunathan Rengaswamy;Vikrant Gangwal;Shankar Narasimhan

  • Approaches for efficient stiction compensation in process control valves

    Ranganathan Srinivasan;Raghunathan Rengaswamy

  • A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops

    Mano Ram Maurya;Raghunathan Rengaswamy;Venkat Venkatasubramanian

  • A modified empirical mode decomposition (EMD) process for oscillation characterization in control loops

    Ranganathan Srinivasan;Raghunathan Rengaswamy;Randy Miller

  • Design of sensor location based on various fault diagnostic observability and reliability criteria

    Mani Bhushan;Raghunathan Rengaswamy

Frequent Co-Authors

Venkat Venkatasubramanian
Venkat Venkatasubramanian Columbia University
Shankar Narasimhan
Shankar Narasimhan Indian Institute of Technology Madras
Pragasen Pillay
Pragasen Pillay Concordia University
Sheldon S. Williamson
Sheldon S. Williamson University of Ontario Institute of Technology
Gregory B. McKenna
Gregory B. McKenna Texas Tech University
Karl-Erik Årzén
Karl-Erik Årzén Lund University

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