Process Intelligence Research
We are the Process Intelligence Reserach group at Delft University of Technology. Our vision is the integration of Artificial Intelligence (AI) and chemical engineering. We will bridge chemical engineering and AI to deliver the next generation of intelligent knowledge and decision-making platforms for the chemical engineering field. At the heart of the successful transformation of chemical engineering with AI lies our fundamental and applied research in machine learning, data science, and process systems engineering.
Reinforcement learning for the design of chemical processes using graph neural networks
Toward autocorrection of chemical process flowsheets using large language models
Generative Artificial Intelligence in Chemical Process Engineering
Flowsheet Recognition using Deep Convolutional Neural Networks
Hurdles in the development of dynamic hybrid semi-parametric models for bioprocess development
Video Tutorial: Graph Neural Network Tool for Predicting Physico-Chemical Properties of Molecules
Graph Neural Networks for Prediction of Fuel Ignition Quality
Lecture on hybrid modeling and optimization of processes
Maximizing the acquisition function of Bayesian optimization to guaranteed global optimality
Hybrid Modeling for the Global Optimization of a Transcritical ORC
Deterministic global nonlinear model predictive control with recurrent neural networks embedded