Artur M. Schweidtmann’s research focuses on computer algorithms from the areas of artificial intelligence (AI), machine learning (ML), and process systems engineering (PSE) with applications in chemical engineering. He develops algorithms and applies them to various chemical engineering domains including robotic chemistry, process optimization, surrogate modeling, and molecular property prediction.
Artur M. Schweidtmann is an assistant professor for chemical engineering at Delft University of Technology. He is heading the ChemEngAI research group at the chemical engineering department. Together with Qian Tao, he is also the director of the “Knowledge driven AI Lab” (KDAI) established through the TU Delft AI Initiative. He received his Master of Science in chemical engineering from RWTH University in 2017. In 2021 he defended his Ph.D. from RWTH in process systems engineering. During his studies, he spent the academic year 2013/2014 at Carnegie Mellon University as a visiting student via the DAAD ISAP program. He performed his Master thesis at the University of Cambridge.
Artificial Intelligence (AI)
Machine Learning (ML)
Process Systems Engineering (PSE)