Ján Drgoňa is an Associate Professor and scientific machine learning leader with a decade of experience developing differentiable programming, constrained optimization, and model predictive control for sustainable energy systems. Currently building a research group at Johns Hopkins after leading SciML efforts at Pacific Northwest National Laboratory, he is the lead developer of influential open-source tools like NeuroMANCER and SLiM that bridge physics-informed modeling and deep learning. His work has driven large multi-million-dollar projects and real-world deployments, including an MPC implementation that halved building energy use while improving thermal comfort by over 30%. Known for mentoring early-career researchers and assembling multi-institution teams, he combines rigorous control-theory foundations with practical software engineering to push data-driven control toward deployment.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Process Control, Doctor of Philosophy - PhD Process Control at Slovenská technická univerzita v Bratislave
Erasmus scholarship Department of Electrical Engineering (ISY) - Automatic Control, Erasmus scholarship Department of Electrical Engineering (ISY) - Automatic Control at Linköping University
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