Congratulations are in order for Professor Paris Perdikaris who has been selected to receive an Air Force’s Young Investigator Research Program (YIP) Award from the Air Force Office of Scientific Research (AFOSR) for his proposal titled:
Self-supervised Learning for Rapid Forecasting, Generalization, and Judicious Decision-making in Dynamic and Stochastic Environments
Abstract:
The machine learning revolution has brought a vast suite of techniques for extracting patterns from data and turn them into actionable knowledge, with growing impact on almost every scientific discipline. However, all of its noticeable successes are demonstrated in very well, and rather narrowly defined problems, where sufficient amounts data exists in order to adequately cover the input domain and effectively interpolate between the observed outputs, while difficulties arise when one seeks to understand causal effects and extrapolate in new, previously unseen, scenarios. In this work, we aspire to develop the fundamental building blocks for a new type of {\em neural computational mathematics} by introducing scalabe and robust statistical inference techniques for accelerating the modeling and simulation of complex physics-based systems. These techniques include the development of novel neural architectures, {\em self-supervised} inference techniques with strong generalization performance, as well as scalable algorithms for aleatoric and epistemic uncertainty quantification. Taken all together, these cross-cutting tools aim to provide effective rules for exploration and judicious decision making under uncertainty that will benefit a wide range of science domains, including applications in design, planning, and control of autonomous systems.