Richard Braatz

Full Professor, Chemical Engineering, Massachusetts Institute of Technology

Joined

July 2019

Names

Richard Braatz

Richard D. Braatz

Richard P. Braatz

Emails

****@mit.edu (Confirmed)

Personal Links

Career & Education History

Full Professor

Chemical Engineering, Massachusetts Institute of Technology (mit.edu)

2010 – Present

Full Professor

Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign (uillinois.edu)

2002 – 2010

Associate Professor

Chemical Engineering, University of Illinois at Urbana-Champaign (uillinois.edu)

2000 – 2002

Advisors, Relations & Conflicts

PhD Advisee

Pedro Seber

2022 – Present

PhD Advisor

Manfred Morari

1988 – 1993

Expertise

physics-informed neural networks

feature design

qualitative mechanistic knowledge

hybrid modeling

lithium-ion batteries

Present

Publications

LCEN: A Nonlinear, Interpretable Feature Selection and Machine Learning Algorithm
Pedro Seber, Richard Braatz
- Accepted by TMLR
- Readers: Everyone
Time-certified input-constrained NMPC via Koopman Operator
Liang Wu, Krystian Ganko, Richard Braatz
- 8th IFAC Conference on Nonlinear Model Predictive Control NMPC 2024
- Readers: Everyone
An Execution-time-certified Riccati-based IPM Algorithm for RTI-based Input-constrained NMPC
Liang Wu, Krystian Ganko, Shimin Wang, Richard Braatz
- 2024 IEEE 63rd Conference on Decision and Control (CDC)
- Readers: Everyone
A Direct Optimization Algorithm for Input-Constrained MPC
Liang Wu, Richard Braatz
- IEEE Transactions on Automatic Control
- Readers: Everyone
Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms
Utkarsh, Valentin Churavy, Yingbo Ma, Tim Besard, Prakitr Srisuma, Tim Gymnich, Adam R. Gerlach, Alan Edelman, George Barbastathis, Richard Braatz, Christopher Vincent Rackauckas
- Computer Methods in Applied Mechanics and Engineering, Volume 419, 2024
- Readers: Everyone
Improving N-Glycosylation and Biopharmaceutical Production Predictions Using AutoML-Built Residual Hybrid Models
Pedro Seber, Richard Braatz
- AISTATS 2025 Poster
- Readers: Everyone
LCEN: A Novel Feature Selection Algorithm for Nonlinear, Interpretable Machine Learning Models
Pedro Seber, Richard Braatz
- Submitted to ICLR 2025
- Readers: Everyone
Lithium-Ion Battery System Health Monitoring and Resistance-Based Fault Analysis from Field Data Using Recursive Spatiotemporal Gaussian Processes
Joachim Schaeffer, Eric Lenz, Duncan Gulla, Martin Z. Bazant, Richard Braatz, Rolf Findeisen
- NeurIPS BDU Workshop 2024 Oral
- Readers: Everyone
Improving Diagnostics and Prognostics of Implantable Cardioverter Defibrillator Batteries with Interpretable Machine Learning Models
Qiaohao Liang, Giacomo Galuppini, Martin Z. Bazant, Richard Braatz
- Arxiv/SSRN
- Readers: Everyone
Automated outlier detection and estimation of missing data
Jinwook Rhyu, Dragana Bozinovski, Alexis B. Dubs, Naresh Mohan, Elizabeth M. Cummings Bende, Andrew J. Maloney, Miriam Nieves, Jose Sangerman, Amos E. Lu, Moo Sun Hong, Anastasia Artamonova, Rui Wen Ou, Paul W. Barone, James C. Leung, Jacqueline M. Wolfrum, Anthony J. Sinskey, Stacy L. Springs, Richard D. Braatz
- Comput. Chem. Eng. 2024
- Readers: Everyone

View all 191 publications

Co-Authors

View all 268 co-authors