November 2025

We will present six talks and a poster at the 2025 AIChE Annual Meeting in Boston:

• A Physics-Informed Machine Learning Framework for Autonomous Additive Manufacturing of Functional Materials (108e @ 3D Printing Fundamentals and Applications Session), November 3, 2025, 9:40 AM - 10:10 AM, 208 Hynes Convention Center Link

• Multimodal Machine Learning for Predictive Structural Characterization of Plant-Based Meat Products in Food Extrusion Processes (124c @ Modeling, Estimation and Control of Industrial Processes Session), November 3, 2025, 1:06 PM - 1:24 PM, 110 Hynes Convention Center Link

• A Data-Driven Transformer-Based Framework for Cyber-Process Incident Detection and State Reconstruction in Highly Integrated Process Systems (243d @ Cybersecurity and Applications for High-Performance Computing in Next-Gen Manufacturing Session), November 3, 2025, 4:48 PM - 5:06 PM, 304 Hynes Convention Center Link

• Data-Driven Discrepancy Quantification in Microkinetic Modeling of Catalytic Processes Via Bayesian Calibration (329f @ Applied Math and Numerical Methods for Industrial Applications Session), November 4, 2025, 2:00 PM - 2:18 PM, 108 Hynes Convention Center Link

• Nonlinear Model Predictive Control of Ammonia Synthesis and Separation Process Using Integrated Surrogate Modeling (391d @ Interactive Session: Systems and Process Control), November 4, 2025, 3:30 PM - 5:00 PM, Exhibit Hall C, Hynes Convention Center Link

• Moving Horizon Dynamic Optimization of a Renewable-Driven Chemical-Energy Community Under Varying Disruptions (467h @ Modeling, Control, and Optimization of Energy Systems Session), November 5, 2025, 9:48 AM - 10:06 AM, 108 Hynes Convention Center Link

• Digital Twin Modeling of Liver-on-a-Chip Systems: Integrated Computational Fluid Dynamics and Biochemical Kinetics for Drug Metabolism Studies (595g @ Applied Math for Biological and Biomedical Systems Session), November 5, 2025, 5:18 PM - 5:36 PM, 111 Hynes Convention Center Link

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October 2025

Our poster on Nonlinear Model Predictive Control of Ammonia Synthesis and Separation Process Using Integrated Surrogate Modeling has been selected as a semi-finalist for the Computing and Systems Technology (CAST) best poster award at the 2025 AIChE Annual Meeting in Boston.

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Dr. Pourkargar received a Faculty Travel Award from the Johnson Cancer Research Center.

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Amirsalar Bagheri and AmirMohammad Ebrahimi received Travel Awards from the K-State Graduate School and Graduate Student Council (GSC). Congratulations, Amirsalar and AmirMohammad!

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September 2025

Our paper on Nonlinear Predictive Regulation of an Integrated Green Hydrogen and Ammonia Production System Under Time-Varying Renewable Energy Supply has been published in Computers and Chemical Engineering. Link

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Connor Albright received a Kansas Water Institute (KWI) Undergraduate Research Scholarship. Congratulations, Connor!

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August 2025

Connor Albright has joined our group as an undergraduate researcher. Welcome, Connor!

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July 2025

Dr. Pourkargar has been honored with a five-year appointment as the Warren and Gisela Kennedy Keystone Research Scholar at Carl R. Ice College of Engineering. 

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Our paper on Self-Attention Transformer Architectures for Cyberattack Detection and Secure State Reconstruction of Integrated Chemical Process Systems has been published in Chemical Engineering Research and Design. Link

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Our three papers have been published in the Proceedings of the American Control Conference (ACC), Denver, CO, 2025:​

• Learning-Based Estimation and Predictive Control of an Ammonia Synthesis Reactor (WeB15.3 @ Chemical Process Control Session) Link

• Nonlinear Model Predictive Control of a Modular Hydrogen-Ammonia and Renewable Energy Generation System (WeB17.5 @ Model Predictive Control Session) Link

• An Adaptive Distributed Architecture for State Estimation and Control of Integrated Process Networks During Operational Transitions (WeC20.5 @ Estimation and Filtering II Session) Link

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June 2025

Our paper on Exploiting MXenes Properties for Coking Resistance of Ni Catalyst in Dry Reforming of Methane has been published in the Journal of Catalysis. Link

 

 

May 2025

Thiago Cabral has successfully defended his doctoral thesis on A Multiscale Modeling Framework for Complex Chemical Processes with Decision-Making Applications. Congratulations, Dr. Cabral!

 

Dr. Pourkargar joined the Terasaki Institute for Biomedical Innovation as a visiting assistant professor.

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Our paper on A Multiphase-Multiphysics Modeling Framework for Nonlinear Predictive Control of Particulate Polysilicon Reactor Systems has been published in Industrial and Engineering Chemistry Research. Link

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April 2025

Thiago Cabral has been selected as the Tim Taylor Department of Chemical Engineering Graduate Student of the Month by the Carl R. Ice College of Engineering at K-State. Congratulations, Thiago!

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Amirsalar Bagheri and AmirMohammad Ebrahimi received Student Travel Awards from the American Automatic Control Council to attend the 2025 American Control Conference in Denver, CO. Congratulations, Amirsalar and AmirMohammad!

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March 2025

Amirsalar Bagheri received the Best Presentation Award at the 2025 K-State Graduate Research, Arts, and Discovery (K-GRAD) Forum. Congratulations, Amirsalar!

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AmirMohammad Ebrahimi received the William H. and Virginia Honstead Graduate Fellowship from the Tim Taylor Department of Chemical Engineering at K-State. Congratulations, AmirMohammad!

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February 2025

Thiago Cabral received the Margaret Ruth Hannah Graduate Cancer Research Award from the Johnson Cancer Research Center. Congratulations, Thiago!

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January 2025

Our paper on A Time-Series Based Hybrid and Physics-Informed Machine Learning Framework to Predict Soil Water Content has been published in Engineering Applications of Artificial Intelligence. Link

 

Our paper on Integrated Learning-Based Estimation and Nonlinear Predictive Control of an Ammonia Synthesis Reactor has been published in the AIChE Journal. Link

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December 2024

Our paper on Multiscale-Multiphysics Predictive Modeling of Chemical Vapor Deposition Processes for Carbon Nanotube Synthesis has been published in Chemical Engineering Science. Link

 

 

November 2024

Dr. Pourkargar received a grant from the National Science Foundation on Physics-Informed Learning-Based Synthesis of Functional Chemical Products for Renewable Energy Applications. Link

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October 2024

We have given six oral presentations and a poster at the 2024 AIChE Annual Meeting in San Diego:

• Keynote 1 - Resilient Multi-Agent Estimation and Control of Complex Process Networks (702a @ Cybersecurity and High-Performance Computing in Next-Gen Manufacturing Session) Link

• Predictive Modeling and Optimal Regulation of Modular Hydrogen-Ammonia Systems with Renewable Energy Integration for Resilient Chemical-Energy Conversion (564d @ Next-Gen Manufacturing in Chemical and Energy Systems Session) Link

• A Physics-Informed Deep Learning Approach to Predict Soil Water Content for Agricultural Decision-Making (579a @ Data-Driven and Hybrid Modeling for Decision-Making Session) Link

• Predictive Modeling and Optimal Control of a Particulate Polysilicon Reactor System for Enhanced Solar Cell Manufacturing (617c @ Modeling, Optimization, and Control in Next-Gen Manufacturing Session) Link

• Dynamic Graph-Based Distributed Estimation and Control of Fast-Evolving Complex Process Networks (664f @ Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency Session) Link

• Time-Series Integrated Surrogate Modeling for Control of Ammonia Synthesis and Adsorption Processes (711a @ AI/ML Modeling, Optimization, and Control Applications II Session) Link

• A Distributed Data-Driven Predictive Modeling Approach for Cyber-Process Incident Identification Using Spectral Community Detection (375d @ Interactive Session: Data and Information Systems) Link

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AmirMohammad Ebrahimi has successfully defended his master's thesis on Distributed Model Predictive Control of Integrated Process Systems Using an Adaptive Community Detection Approach. Congratulations, AmirMohammad!

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Our paper on Multi-Agent Distributed Control of Integrated Process Networks Using an Adaptive Community Detection Approach has been published in Digital Chemical Engineering. Link

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Thiago Cabral received the Gary Wurdeman-Vanier Family Scholarship from the Tim Taylor Department of Chemical Engineering at K-State. Congratulations, Thiago!

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September 2024

Our paper on An Adaptive Distributed Architecture for Multi-Agent State Estimation and Control of Complex Process Systems has been published in Chemical Engineering Research and Design. Link

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Our paper on Predictive Modeling and Robust Nonlinear Control of a Polysilicon Reactor System for Enhanced Solar Cell Production has been published in Control Engineering Practice. Link

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Dr. Pourkargar received the Carl R. Ice College of Engineering Outstanding Assistant Professor Award. Link

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July 2024

Our three papers have been published in the Proceedings of the American Control Conference (ACC), Toronto, Canada, 2024:

• Learning-Based Model Predictive Control of an Ammonia Synthesis Reactor Link

• Distributed Model Predictive Control of Integrated Process Networks Based on an Adaptive Community Detection Approach Link

• A Physics-Informed Machine Learning Approach to Predict Soil Water Content for Agricultural Decision-Making Link

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Our two papers have been published in the Proceedings of the 12th IFAC Symposium on Advanced Control of Chemical Processes (ADCHE), Toronto, Canada, 2024:

• Nonlinear Model Predictive Control of a Particulate Polysilicon Reactor System for Enhanced Solar Cell Production Link

• Distributed Estimation and Control of Process Networks Using Adaptive Community Detection Link

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June 2024

Our paper on Learning-Based Model Reduction and Predictive Control of an Ammonia Synthesis Process has been published in Industrial and Engineering Chemistry Research. Link

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May 2024

Dr. Pourkargar joined the Terasaki Institute for Biomedical Innovation as a visiting assistant professor.

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Dr. Pourkargar received a Global Food Systems Seed Grant from the K-State Office of the Vice President for Research on A Physics-Informed Machine Learning-Based Predictive Modeling Framework to Enhance Efficiency, Sustainability, and Resilience for Global Food Systems. Link

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April 2024

Carlos Veloz Marmolejo has successfully defended his master's thesis on Predictive Modeling and Optimization-Based Control of Particulate Polysilicon Reactor Systems for Enhanced Solar Cell Production. Congratulations, Carlos!

 

Oladotun Osisami has successfully defended his master's thesis on Machine Learning-Based Cancer Prediction Using Large Scale Clinical Data. Congratulations, Ola!

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Amirsalar Bagheri has successfully defended his master's thesis on Applications of Deep Learning and Time-Series Analysis in Dynamic Process Optimization and Decision Making. Congratulations, Amirsalar!

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March 2024

Amirsalar Bagheri presented a poster on Renewable Energy-Based Ammonia Production at the Kansas Capitol.

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Carlos Veloz Marmolejo has been selected as the Tim Taylor Department of Chemical Engineering Graduate Student of the Month by the Carl R. Ice College of Engineering at K-State. Congratulations, Carlos!

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Kansas Public Radio interviewed Dr. Pourkargar, highlighting his research on applying physics-informed machine learning to organ-on-a-chip systems for drug discovery. Link

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January 2024

AmirMohammad Ebrahimi has been selected as the Tim Taylor Department of Chemical Engineering Graduate Student of the Month by the Carl R. Ice College of Engineering at K-State. Congratulations, AmirMohammad!

 

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November 2023

Dr. Pourkargar received a grant from the National Science Foundation on Physics-Informed Machine Learning with Organ-on-a-Chip Data for an In-Depth Understanding of Disease Progression and Drug Delivery Dynamics. Link

 

We have given two oral presentations at the 2023 AIChE Annual Meeting in Orlando:

• Learning-Based Data Reconstruction and Predictive Modeling of an Ammonia Synthesis Process for State Estimation and Control Applications (207d @ Advances in Process Control I Session) Link

• Distributed Estimation and Model Predictive Control of Integrated Nonlinear Process Systems Using an Adaptive Community Detection Approach (295d @ Advances in Process Control II Session) Link

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Amirsalar Bagheri has been selected as the Tim Taylor Department of Chemical Engineering Graduate Student of the Month by the Carl R. Ice College of Engineering at K-State. Congratulations, Amirsalar!

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October 2023

Amirsalar Bagheri was recognized at K-State's Research and the State Forum for his poster on Application of Artificial Intelligence in Optimizing Green Ammonia Production. Congratulations, Amirsalar!

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Thiago Cabral received the William H. and Virginia Honstead Graduate Fellowship from the Tim Taylor Department of Chemical Engineering at K-State. Congratulations, Thiago!

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August 2023

Dr. Pourkargar joined the Food Science Institute at K-State as a Graduate Faculty.

 

 

July 2023

Dr. Pourkargar received the Big XII Faculty Fellowship from K-State.

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June 2023

Our paper on Cyberattack Awareness and Resiliency of Integrated Moving Horizon Estimation and Model Predictive Control of Complex Process Networks has been published in the Proceedings of the American Control Conference (ACC), San Diego, CA, 2023. Link

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Oladotun Osisami has joined our group as a graduate student. Welcome, Ola!

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May 2022

Amirsalar Bagheri and AmirMohammad Ebrahimi have successfully passed their PhD qualifying exams. Congratulations, Amirsalar and AmirMohammad!

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April 2023

Gregory Gause has successfully defended his master's thesis on Computational Modeling of Food Extrusion Systems for Optimal Plant-Based Meat Production. Congratulations, Greg!

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March 2023

Dr. Pourkargar received the AFOSR Summer Faculty Fellowship.

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Dr. Pourkargar received the Kansas EPSCoR First Award for a project on Distributed Green Ammonia Generation for Resilient Energy Storage and Fertilizer Production in Rural Communities. Link

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November 2022

We have given three oral presentations at the 2022 AIChE Annual Meeting in Phoenix:

• A Deep Learning-Based Model Reduction and Control of an Ammonia Synthesis Process (12f @ Data-Driven Dynamic Modeling, Estimation, and Control I Session) Link

• Optimization-Based Estimation and Control of Renewable Energy-Powered Greenhouse Systems (484d @ Modeling, Estimation, and Control Applications Session) Link

• Model Predictive Control of Green-Powered Zero Waste Urban Plant Factories for Sustainable Food Production (587f @ Modeling, Control, and Optimization of Energy Systems I Session) Link

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Blake Karawan has successfully defended his master's thesis on Developing a CFD-Based Axial Compartment Model for a Lab-Scale Bioreactor. Congratulations, Blake!

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Thiago Cabral has been selected as the Tim Taylor Department of Chemical Engineering Graduate Student of the Month by the Carl R. Ice College of Engineering at K-State. Congratulations, Thiago!

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August 2022

Our paper on An Integrated Moving Horizon Estimation and Model Predictive Control Framework for Semi-Closed Greenhouse Systems has been published in the Proceedings of the IEEE Conference on Control Technology and Applications (CCTA), Trieste, Italy, 2022. Link

 

Connor Smith has successfully defended his master's thesis on Data Assisted Modeling of the Liver Organ on a Chip Dynamics. Congratulations, Connor!

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AmirMohammad Ebrahimi and Carlos Veloz Marmolejo have joined our group as graduate students. Welcome, AmirMohammad and Carlos!

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Dr. Pourkargar joined the Johnson Cancer Research Center at K-State as a Faculty Researcher.

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May 2022

Gregory Gause has joined our group as a graduate student. Welcome, Greg!

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Thiago Cabral has successfully passed his PhD qualifying exam. Congratulations, Thiago!

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January 2022

Amirsalar Bagheri, Connor Smith, Jonathon Kohl, and Blake Karawan have joined our group as graduate students. Welcome, Amir, Connor, Jonathon, and Blake!

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November 2021

We have given two oral presentations at the 2021 AIChE Annual Meeting in Boston:

• Output Feedback Control of Nonlinear Distributed Parameter Systems with Unknown Parameters Using a Two-Tier Adaptive Identification Method (105d @ Advances in Process Control I Session) Link

• Model Predictive Control of Integrated Energy and Chemical Manufacturing Systems (537h @ Modeling, Control, and Optimization of Energy Systems II Session) Link

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October 2021

Brayden Sundberg has joined our group as an undergraduate researcher. Welcome, Brayden!

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August 2021

Our paper on Lyapunov-Based Online Model Reduction and Control of Semilinear Dissipative Distributed Parameter Systems with Minimum Feedback Information has been published in the Journal of Process Control. Link

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May 2021

Our paper on Distributed Model Predictive Control of Integrated Process Networks: Optimal Decomposition for Varying Operating Points has been published in the Proceedings of the American Control Conference (ACC), New Orleans, LA, 2021. Link

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Thiago Cabral has joined our group as a graduate student. Welcome, Thiago!

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April 2021

Ashton Gohman won first place at the Carl R. Ice College of Engineering Undergraduate Research and Creative Inquiry Showcase for his work on Spatiotemporal Dynamic Modeling of Planar Solid Oxide Fuel Cells. Congratulations, Ashton! Link

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January 2021

Patrick Hinkel has joined our group as an undergraduate researcher. Welcome, Patrick!

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December 2020

Ashton Gohman has joined our group as an undergraduate researcher. Welcome, Ashton!

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November 2020

We have given three oral presentations at the 2020 AIChE Annual Meeting:

• Output Feedback Control of Integrated Lumped and Distributed Parameter Systems Using Mobile Sensors Network (172g @ Advances in Process Control Session) Link

• Distributed Model Predictive Control of Integrated Process Networks Using Community Detection (687g @ Optimization-based Estimation and Control Session) Link

• Constrained Control of Dissipative Distributed Parameter Systems via On-Demand Data-Driven Model Reduction (399a @ Advanced Modelling and Data Systems Applications in Next-Gen Manufacturing II Session) Link

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July 2020

Our paper on Control of Semilinear Dissipative Distributed Parameter Systems with Minimum Feedback Information has been published in the Proceedings of the American Control Conference (ACC), Denver, CO, 2020. Link

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Dr. Pourkargar joined the Tim Taylor Department of Chemical Engineering at K-State. He is starting up a multidisciplinary research group in the area of sustainable and intelligent process systems engineering.