Transforming chemical engineering with artificial intelligence
What is Process Intelligence Research?
We are a research group at the Department of Chemical Engineering at the 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.
Research themes
Process Systems Engineering (PSE) is a vital sub-discipline within Chemical Engineering, focusing on the holistic understanding and development of generalized Chemical Engineering models. By integrating knowledge from various fields within Chemical Engineering and the Physical Sciences, PSE employs a systems-thinking approach to abstract from the physical environment and precisely frame problems before model construction. These generalized models bridge practical engineering applications with theoretical conceptualization, ensuring that pertinent questions are prioritized from the outset.
Our research emphasizes the integration of Artificial Intelligence (AI) in PSE, aiming to enhance model accuracy, efficiency, and predictive capabilities. By leveraging AI, we seek to develop intelligent systems that optimize processes, drive innovation, and achieve superior outcomes in Chemical Engineering.
Latest News
The Nobel Prize in Physics 2024 was awarded to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks"
On November 19th, Artur will give an IChemE Webinar on digitizing Piping and Instrumentation Diagrams (P&IDs) using deep learning. We develop computer vision techniques for accurately recognizing symbols, lines, text, and tables on P&IDs. Then, we translate those to industry smartP&ID data standards such as DEXPI
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