Joel Paulson

Citation name

Paulson, J.

Affiliation

The Ohio State University

State

OH

Country

USA

Joel Paulson is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at The Ohio State University where he is also a core faculty member of the Sustainability Institute (SI) and an affiliate of the Translational Data Analytics Institute (TDAI). His research focuses on data-driven optimization and control of complex systems under uncertainty with applications in next-generation biochemical and smart manufacturing processes such as continuous pharmaceutical manufacturing, colloidal self-assembly, and non-equilibrium plasma jets.

Sessions chaired or co-chaired

Advances in Computational Methods and Numerical Analysis - I

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Advances in Computational Methods and Numerical Analysis - II

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Advances in Computational Methods and Numerical Analysis II

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Advances in Process Control I

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Advances in Process Control II

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency I

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency I

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency II

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Big Data and Applications in Advanced Modeling and Manufacturing

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Data-Driven Dynamic Modeling, Estimation and Control III

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Invited Tutorial Session - Approaches in Data Analytics I

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Invited Tutorial Session - Approaches in Data Analytics II

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

Modeling, Control and Optimization of Manufacturing Systems2023 Spring Meeting and 19th Global Congress on Process Safety

Predictive Control and Optimization2023 Spring Meeting and 19th Global Congress on Process Safety

Authored

(17f) Learning-Based MPC with State-Dependent Uncertainty Using Adaptive Scenario Trees

Angelo D. Bonzanini

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(299f) Fast Approximate Multistage NMPC with Online Scenario Tree Generation Using Active Deep Learning

Angelo D. Bonzanini

Georgios Makrygiorgos

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(434g) Goal-Oriented Model Learning with High-Fidelity Simulations Using MPC-Embedded Bayesian Optimization

Farshud Sorourifar

Georgios Makrygiorgos

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

(718c) Towards Integration of Design and Operation of Techno-Ecological Synergistic Systems

2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)

Accelerating Multiscale Process Design with Bayesian Optimization: Progress, Challenges, and Opportunities

2021 Process Development Symposium

(182d) Physics-Constrained Deep Learning of Unmodeled Physics in Systems Governed By Stochastic Differential Equations

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(176h) Robust Data-Driven Design of Generic Control Structures with Probabilistic Guarantees Using Gaussian Process Emulators

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(644c) Deep Learning-Based Approximate Economic Model Predictive Control with Offset-Free Asymptotic Performance Guarantees Using a Modifier-Adaptation Scheme

Dinesh Krishnamoorthy

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(485a) Integrated Design and Model Predictive Control of Multiscale Systems Using a Multi-Fidelity Bayesian Optimization Approach

Farshud Sorourifar

Naitik A. Choksi

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(434b) Enabling Real-Time Synergies in Techno-Ecological Systems Using Adaptive Nonlinear Model Predictive Control

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

(558a) A Novel Constrained Bayesian Optimization Method for Computationally Expensive Grey-Box Models with Composite Objective and Constraint Functions

2021 Annual Meeting (ISBN: 978-0-8169-1116-5)

A Tutorial on Physics-Informed Bayesian Optimization for Multi-Scale Process Design and Operation

2022 Spring Meeting and 18th Global Congress on Process Safety Proceedings

(433h) Continuous Multi-Fidelity Bayesian Optimization for Efficient Integrated Process Design and Advanced Control

Farshud Sorourifar

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(12a) Active Deep Learning for Scalable Approximation of Reachable and Invariant Sets for Mixed-Integer Nonlinear Systems

Angelo D. Bonzanini

Georgios Makrygiorgos

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(10d) Exact Penalty Bayesian Optimization: No-Regret Data-Driven Optimization with Unknown Equality and Inequality Constraints

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(235f) Data-Efficient Globally Optimal Policy-Based Reinforcement Learning Via Gradient-Accelerated Bayesian Optimization

Georgios Makrygiorgos

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(434a) End-to-End Design and Implementation of Robust MPC on Resource-Limited Hardware Using Multi-Objective Bayesian Optimization and Deep Learning

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(624d) Data-Efficient Automated Tuning of Generic Control Structures Using Adversarially Robust Bayesian Optimization

Georgios Makrygiorgos

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(234f) Exploiting Grey-Box Hybrid Models in Constrained Bayesian Optimization Using a Smoothed Sample Average Approximation

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(483c) Constrained Robust Bayesian Optimization of Expensive Black-Box Functions Under Uncertainty

Farshud Sorourifar

2022 Annual Meeting (ISBN: 978-0-8169-1118-9)

(150b) The Next Epoch of Model Predictive Control: Exploiting Machine Learning Methods for Approximation and Design

2023 Spring Meeting and 19th Global Congress on Process Safety

Associated proceedings

2020 Virtual AIChE Annual Meeting

2021 Process Development Symposium

2021 Annual Meeting

2022 Spring Meeting and 18th Global Congress on Process Safety Proceedings

2022 Annual Meeting

2023 Spring Meeting and 19th Global Congress on Process Safety