Sivaguru S. Sritharan

Sivaguru S. Sritharan (also known as S. S. Sritharan) is an American aerodynamicist and mathematician.

Sritharan served in civilian universities such as University of Southern California and University of Wyoming as faculty member and head of the department and also in the Department of Defense (U. S. Navy and U. S. Air Force) in various capacities ranging from scientist to leadership roles, and also held visiting positions at several international institutions.

He also delivered a keynote address at the forum examining the evolution of algorithmic finance and its convergence with advanced mathematics and artificial intelligence.

Contributions Sritharan is known for his research contributions in rigorous mathematical theory, optimal control and stochastic analysis of fluid mechanics and magneto-hydrodynamics.

His notable contributions include:

1. Developing dynamic programming method for the equations of fluid dynamics. This subject is closely related to reinforcement learning in the language of machine learning.

2. First complete proof of the Pontryagin’s Maximum Principle for fluid dynamic equations with state constraints, as a joint work with UCLA mathematician Hector. O. Fattorini.

3. Developing robust (H-infinity) control theory for fluid dynamics as a joint work with Romanian mathematician Viorel P. Barbu.

4. First successful rigorous theory establishing a direct stochastic analogy to the famous Jacques-Louis Lions and G. Prodi (1959) on existence and uniqueness theorem for the two dimensional Navier-Stokes equation as a joint work with J. L. Menaldi utilizing a subtle local monotonicity property.

5. Proving Large Deviation Principle for stochastic Navier-Stokes equation as a joint work with P. Sundar to estimate the probability of rare events.

6. Systematic development of differential geometric methods for aerodynamics of supersonic delta wings.

7. Advancing geometric theory of hydrodynamic transition to turbulence.

8. Developing nonlinear filtering theory for stochastic Navier-Stokes equations for the estimation of turbulence based on partial measurements and similar theories for models describing quantum dynamics.