Scheduled presentations:

• Kaplan Hydraulic Turbine Optimization against Cavitation using a Continuous Adjoint Method for Two-phase Flows
  *S. Stalikas (Andritz Hydro GmbH), E. Kontoleontos (Andritz Hydro GmbH), K. Giannakoglou (National Technical University of Athens)
• Scientific Machine Learning for Modeling and Control
  *J. Drgona (Johns Hopkins University)
• Balanced Active Subspaces for Optimal Control of High-Dimensional Fluid Flows via Trajectory Optimization.
  E. Ameh (CORNELL UNIVERSITY), *S. Otto (CORNELL UNIVERSITY)
• Physics-Enhanced Reinforcement Learning for Real-time Optimal Control of Dynamical Systems
  *M. Tomasetto (Politecnico di Milano), N. Botteghi (Politecnico di Milano), G. Bruni (Politecnico di Milano), A. Manzoni (Politecnico di Milano)
• Improving the Efficiency of Learning Fluid Flow Control Policies Using Gradients from Differentiable Simulators and Data-Driven Surrogate Models
  *M. Straat (Bielefeld University), S. Mokbel (University of Washington), N. Zolman (University of Washington), S. Brunton (University of Washington)
• Gradient-enhanced control of turbulent flow with differentiable simulation
  *S. Mokbel (University of Washington), C. Lagemann (University of Washington), E. Lagemann (University of Washington), S. Brunton (University of Washington)