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Richard D. Braatz

Richard D. Braatz

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
91
Citations
31169
World Ranking
286
National Ranking
140

Research.com Recognitions

  • 2019 - Member of the National Academy of Engineering For contributions to diagnosis and control of large-scale and molecular processes for materials, microelectronics and pharmaceuticals manufacturing.
  • 2008 - Fellow of the International Federation of Automatic Control (IFAC)
  • 2008 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2007 - IEEE Fellow For contributions to robust control of industrial systems

Overview

Richard D. Braatz is affiliated with MIT in the United States and has contributed extensively to research at the intersection of engineering and biochemistry, genetics, and molecular biology. Their work spans several specialized subfields, including molecular biology, control and systems engineering, electrical and electronic engineering, automotive engineering, and materials chemistry.

The scientist's research topics cover various advanced technological and biological areas, notably:

  • Advanced Battery Technologies Research
  • Viral Infectious Diseases and Gene Expression in Insects
  • Advancements in Battery Materials
  • Fault Detection and Control Systems
  • Advanced Control Systems Optimization
  • Protein purification and stability
  • Advanced Battery Materials and Technologies

Richard D. Braatz has published numerous papers in well-known academic venues. Frequent publication sites include:

  • arXiv (Cornell University)
  • Computers & Chemical Engineering
  • Journal of The Electrochemical Society
  • Biotechnology and Bioengineering
  • IFAC-PapersOnLine

Noteworthy recent papers reflect the scientist's involvement in battery research, electrochemical processes, and gene therapies. These include:

  • Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments, 2022, Chemical Society Reviews
  • Closed-loop optimization of fast-charging protocols for batteries with machine learning, 2020, Nature
  • Perspective-Combining Physics and Machine Learning to Predict Battery Lifetime, 2021, Journal of The Electrochemical Society
  • Fictitious phase separation in Li layered oxides driven by electro-autocatalysis, 2021, Nature Materials
  • Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies, 2021, Molecular Therapy - Methods & Clinical Development

The scientist collaborates frequently with colleagues, including:

  • Martin Z. Bazant
  • Allan S. Myerson
  • Anthony J. Sinskey
  • Jacqueline M. Wolfrum
  • Stacy L. Springs

In recognition of their contributions, Richard D. Braatz has received several awards. They became a Member of the National Academy of Engineering in 2019 for work on diagnosis and control of large-scale and molecular processes related to materials, microelectronics, and pharmaceuticals manufacturing.

Additional honors include being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2008 and a Fellow of the International Federation of Automatic Control (IFAC) in the same year. The scientist was also recognized as an IEEE Fellow in 2007 for contributions to robust control of industrial systems.

Best Publications

  • Data-driven prediction of battery cycle life before capacity degradation

    Kristen A. Severson;Peter M. Attia;Norman Jin;Nicholas Perkins

  • Fault Detection and Diagnosis in Industrial Systems

    Leo H. Chiang;Evan L. Russell;Richard D. Braatz

  • Closed-loop optimization of fast-charging protocols for batteries with machine learning.

    Peter M. Attia;Aditya Grover;Norman Jin;Kristen A. Severson

  • Modeling and Simulation of Lithium-Ion Batteries from a Systems Engineering Perspective

    Venkatasailanathan Ramadesigan;Paul W. C. Northrop;Sumitava De;Shriram Santhanagopalan

  • A tutorial on linear and bilinear matrix inequalities

    Jeremy G. VanAntwerp;Richard D. Braatz

  • Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis

    Leo H Chiang;Evan L Russell;Richard D Braatz

  • End‐to‐End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation

    Salvatore Mascia;Patrick L. Heider;Haitao Zhang;Richard Lakerveld

  • Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis

    Evan L. Russell;Leo H. Chiang;Richard D. Braatz

  • Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes

    Evan L. Russell;Leo H. Chiang;Richard D. Braatz

  • Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review

    Levente L. Simon;Hajnalka Pataki;György Marosi;Fabian Meemken

  • First-principles and direct design approaches for the control of pharmaceutical crystallization

    Mitsuko Fujiwara;Zoltan K. Nagy;Jie W. Chew;Richard D. Braatz

  • Mathematical modeling of drug delivery from autocatalytically degradable PLGA microspheres--a review

    Ashlee N. Ford Versypt;Daniel W. Pack;Daniel W. Pack;Richard D. Braatz;Richard D. Braatz

  • High resolution algorithms for multidimensional population balance equations

    Rudiyanto Gunawan;Irene Fusman;Richard D. Braatz

  • Advances and new directions in crystallization control

    Zoltan K. Nagy;Richard D. Braatz

  • Robust nonlinear model predictive control of batch processes

    Zoltan K. Nagy;Richard D. Braatz

  • Paracetamol Crystallization Using Laser Backscattering and ATR-FTIR Spectroscopy: Metastability, Agglomeration, and Control

    Mitsuko Fujiwara;Pui Shan Chow;and David L. Ma;Richard D. Braatz

  • LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control

    Marcello Torchio;Lalo Magni;R. Bhushan Gopaluni;Richard D. Braatz

  • Advanced control of crystallization processes

    Richard D. Braatz

  • Constrained zonotopes

    Joseph K. Scott;Davide M. Raimondo;Giuseppe Roberto Marseglia;Richard D. Braatz

  • Switched model predictive control of switched linear systems

    Lixian Zhang;Songlin Zhuang;Richard D. Braatz

  • Open-loop and closed-loop robust optimal control of batch processes using distributional and worst-case analysis

    Zoltan K. Nagy;Zoltan K. Nagy;Richard D. Braatz

  • Improved Filter Design in Internal Model Control

    Ian G. Horn;Jeffery R. Arulandu;Christopher J. Gombas;Jeremy G. VanAntwerp

  • Stochastic nonlinear model predictive control with probabilistic constraints

    Ali Mesbah;Stefan Streif;Rolf Findeisen;Richard D. Braatz

  • Designer Dual Therapy Nanolayered Implant Coatings Eradicate Biofilms and Accelerate Bone Tissue Repair

    Jouha Min;Ki Young Choi;Erik C. Dreaden;Robert F. Padera

  • Modelling and control of combined cooling and antisolvent crystallization processes

    Zoltan K. Nagy;M. Fujiwara;Richard D. Braatz

  • Computational complexity of µ calculation

    Richard D. Braatz;Peter M. Young;John C. Doyle;Manfred Morari

  • Distributional uncertainty analysis using power series and polynomial chaos expansions

    Z.K. Nagy;R.D. Braatz

  • Model Predictive Control

    Andrew P. Featherstone;Jeremy G. VanAntwerp;Richard D. Braatz

  • Computational complexity of μ calculation

    Richard D. Braatz;Peter M. Young;John C. Doyle;Manfred Morari

  • On the "Identification and control of dynamical systems using neural networks"

    E. Rios-Patron;R.D. Braatz

Frequent Co-Authors

Richard C. Alkire
Richard C. Alkire University of Illinois at Urbana-Champaign
Rolf Findeisen
Rolf Findeisen Technical University of Darmstadt
Manfred Morari
Manfred Morari University of Pennsylvania
Lalo Magni
Lalo Magni University of Pavia
Charles F. Zukoski
Charles F. Zukoski University of Illinois at Urbana-Champaign
Paul J. A. Kenis
Paul J. A. Kenis University of Illinois at Urbana-Champaign
Stephen J. Harris
Stephen J. Harris Lawrence Berkeley National Laboratory
William C. Chueh
William C. Chueh Stanford University

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