Research Areas Differentiable programming Scientific machine learning for dynamical systems, optimization, and control Building energy systems Process control

Ján Drgoňa is an incoming associate research professor in the department of Civil and Systems Engineering and a member of the Ralph S. O’Connor Sustainable Energy Institute.

His innovative research centers on differentiable programming and scientific machine learning (SciML) for dynamical systems, optimization, and control. He has particular experience in the deployment of machine learning and advanced control methods for real-world applications, including building energy systems and industrial process control.

Previously, Drgoňa was a principal investigator and research data scientist at Pacific Northwest National Laboratory (PNNL) where he served as the lead software developer of Neuromancer SciML library for learning to solve constrained optimization, physics-informed machine learning, and optimal control problems. Within two years, the library became the most popular open-source repository released by PNNL.

Drgoňa is a member of the Institute of Electrical and Electronics Engineers and the Association for Computing Machinery. He regularly serves as a reviewer for related journals including Applied Energy, Automatica, IEEE Control Systems Letters, IEEE Transactions on Control Systems Technology, IEEE Transactions on Industrial Informatics, Control Engineering Practice, Journal of Process Control, Energy and Buildings, Journal of Control Automation and Electrical Systems, and Electric Power Systems Research.

Drgoňa earned his BSc, MSc, and PhD in control engineering from the Institute of Information Engineering, Automation, and Mathematics at the Slovak University of Technology. Prior to his work with PNNL, he held a postdoctoral position in the Mechanical Engineering Department at KU Leuven in Belgium.