We are an interdisciplinary research group in the Department of Civil and Systems Engineering affiliated with the Ralph S. O’Connor Sustainable Energy Institute (ROSEI) and Data Science and AI Institute (DSAI) at Johns Hopkins University (JHU). We do research at the intersection of machine learning, optimization, control, and energy systems.
- Ján Drgoňa (PI)
- Pietro Zanotta (PhD student)
- Honghui Zheng (PhD student)
- Parv Khurana (postdoc)
- Liang Wu (postdoc)
- Leandro Von Krannichfeldt (visiting PhD student)
- Alireza Daneshvar
- Guangyu Wu
- Gonzalo Borrego Acosta (MSc student)
- scientific machine learning (SciML)
- differentiable programming
- physics-informed machine learning (PIML)
- learning to optimize (L2O)
- learning to control (L2C)
- model predictive control (MPC)
- nonlinear system identification
- sustainable energy systems applications
Our group maintains and contributes to several open-source SciML repositories.
