World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
48
Citations
7699
World Ranking
3117
National Ranking
1170

Overview

Jose A. Romagnoli is affiliated with Louisiana State University in the United States. The main field of their research is Engineering, with a focus on several subfields including Control and Systems Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Materials Chemistry, and Biomedical Engineering.

Their work covers a range of topics, particularly:

  • Fuel Cells and Related Materials
  • Fault Detection and Control Systems
  • Advanced Control Systems Optimization
  • Mineral Processing and Grinding
  • Process Optimization and Integration
  • Machine Learning in Materials Science
  • Membrane-based Ion Separation Techniques

Jose A. Romagnoli has contributed extensively to academic literature, including several recent publications such as:

  • "Investigation of transfer learning for image classification and impact on training sample size" (2021), published in Chemometrics and Intelligent Laboratory Systems
  • "Electrochemical Pumping for Challenging Hydrogen Separations" (2022), published in ACS Energy Letters
  • "Data-based health indicator extraction for battery SOH estimation via deep learning" (2023), published in Journal of Energy Storage
  • "Machine-learning-based simulation and fed-batch control of cyanobacterial-phycocyanin production in Plectonema by artificial neural network and deep reinforcement learning" (2020), published in Computers & Chemical Engineering
  • "Operation optimization of a cryogenic NGL recovery unit using deep learning based surrogate modeling" (2020), published in Computers & Chemical Engineering

The scientist frequently publishes in various venues, with multiple publications in:

  • Industrial & Engineering Chemistry Research (7 publications)
  • Computers & Chemical Engineering (6 publications)
  • IFAC-PapersOnLine (4 publications)
  • Systems and Control Transactions (3 publications)
  • Chemometrics and Intelligent Laboratory Systems (2 publications)

Collaborations are a notable aspect of Romagnoli's research activities. Frequent co-authors include:

  • Luis Briceño-Mena (17 joint publications)
  • Christopher G. Arges (12 joint publications)
  • Jorge Chebeir (10 joint publications)
  • Roberto Baratti (9 joint publications)
  • Teslim Olayiwola (9 joint publications)

Best Publications

  • Data Processing and Reconciliation for Chemical Process Operations

    Jose A. Romagnoli;Mabel Cristina Sanchez

  • Model predictive control based on Wiener models

    Sandra J. Norquay;Ahmet Palazoglu;JoséA. Romagnoli

  • Integrated flexibility and controllability analysis in design of chemical processes

    Parisa A. Bahri;Jose A. Bandoni;Jose A. Romagnoli

  • Process synthesis and optimisation tools for environmental design: methodology and structure

    Brett Alexander;Geoff Barton;Jim Petrie;Jose Romagnoli

  • Application of Wiener model predictive control (WMPC) to a pH neutralization experiment

    S.J. Norquay;A. Palazoglu;J.A. Romagnoli

  • Antisolvent crystallization: Model identification, experimental validation and dynamic simulation

    S. Mostafa Nowee;Ali Abbas;Jose A. Romagnoli

  • Introduction to process control

    Jose A. Romagnoli;Ahmet Palazoglu

  • Rectification of process measurement data in the presence of gross errors

    J.A. Romagnoli;G. Stephanopoulos

  • Continuous control of a polymerization system with deep reinforcement learning

    Yan Ma;Wenbo Zhu;Michael G. Benton;José Romagnoli

  • Operation of semi-batch emulsion polymerisation reactors: Modelling, validation and effect of operating conditions

    J. Zeaiter;J. A. Romagnoli;G. W. Barton;V. G. Gomes

  • Robust multi-scale principal components analysis with applications to process monitoring

    D. Wang;J.A. Romagnoli

  • On the rectification of measurement errors for complex chemical plants: Steady state analysis

    J.A. Romagnoli;G. Stephanopoulos

  • Dynamic sensing using intelligent composite: an investigation to development of new pH sensors and electrochromic devices

    A. Talaie;J.Y. Lee;Y.K. Lee;J. Jang

  • Real-time implementation of multi-linear model-based control strategies––an application to a bench-scale pH neutralization reactor

    Omar Galán;Jose A Romagnoli;Ahmet Palazoglu

  • Effect of disturbances in optimizing control: Steady‐state open‐loop backoff problem

    Parisa A. Bahri;Jose A. Bandoni;Jose A. Romagnoli

  • Gap Metric Concept and Implications for Multilinear Model-Based Controller Design

    Omar Galán;Jose A. Romagnoli;Ahmet Palazoǧlu, ,§ and;Yaman Arkun

  • Use of orthogonal transformations in data classification-reconciliation

    Mabel Sánchez;José Romagnoli

  • Data mining and clustering in chemical process databases for monitoring and knowledge discovery

    Michael C. Thomas;Wenbo Zhu;Jose A. Romagnoli

  • Sonocrystallisation of sodium chloride particles for inhalation

    Ali Abbas;Mourtada Srour;Patricia Tang;Herbert Chiou

  • Dynamic probabilistic model-based expert system for fault diagnosis

    David Leung;Jose Romagnoli

  • A Framework for Robust Data Reconciliation Based on a Generalized Objective Function

    D. Wang;J. A. Romagnoli

  • Application of Wiener model predictive control (WMPC) to an industrial C2-splitter

    S.J Norquay;A Palazoglu;J.A Romagnoli

  • Simultaneous estimation of biases and leaks in process plants

    Mabel Sánchez;José Romagnoli;Qiyou Jiang;Miguel Bagajewicz

  • Economic impact of disturbances and uncertain parameters in chemical processes—A dynamic back-off analysis

    J.L. Figueroa;P.A. Bahri;J.A. Bandoni;J.A. Romagnoli

  • Optimization in seeded cooling crystallization: A parameter estimation and dynamic optimization study

    S. Mostafa Nowee;Ali Abbas;Jose A. Romagnoli

  • Robust H∞ control of nonlinear plants based on multi-linear models : an application to a bench-scale pH neutralization reactor

    Omar Galán;José A Romagnoli;Ahmet Palazoglu

  • A multi-scale orthogonal nonlinear strategy for multi-variate statistical process monitoring

    A. Maulud;D. Wang;J.A. Romagnoli

Frequent Co-Authors

Pieter Stroeve
Pieter Stroeve University of California, Davis
Graham C. Goodwin
Graham C. Goodwin University of Newcastle Australia
Jin Jang
Jin Jang Kyung Hee University
Yaman Arkun
Yaman Arkun Koç University
João B. P. Soares
João B. P. Soares University of Alberta

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