Uncertainty Quantification (UQ) emerges as a guiding force in the turbulent sea of data-driven domains, from energy to health. This talk presents a methodology that harnesses UQ for robust renewable energy forecasting, employing a stochastic differential equation model that sails beyond the challenges of wind and solar predictability. Shifting the focus to biomedical imaging, we unveil a novel UQ approach that dives into the depths of MRI analysis, providing more precise insights into cardiac health without being anchored to specific segmentation techniques. Embark on a voyage that highlights how navigating the uncertainties of today with UQ can steer us toward the precision of tomorrow's applications. The recorded talk can be found here.
