In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

Black-box optimization, particularly Bayesian optimization, is a practical approach for weather-intervention design, achieving meaningful rainfall ...