Summary
Kartik Krishna is a postdoctoral researcher and applied mathematician with a decade of experience developing theory-driven computational tools at the intersection of nonlinear dynamics, control, and data-driven geometry. His PhD work produced practical methods for sensing and low-energy control of autonomous vehicles in unsteady fluid flows, and he has linked Hamilton–Jacobi–Bellman optimal control theory and reinforcement learning to invariant manifolds in chaotic systems. Currently at WashU Mallinckrodt Institute of Radiology he models brain dynamics as low-dimensional attractors to interpret resting-state fMRI. Kartik combines rigorous PDE and dynamical-systems analysis with hands-on algorithm design inspired by Koopman operator theory, enabling both theoretical insight and implementable control strategies. Based in Missouri, he brings a rare blend of fluid-mechanics intuition and applied topology for data analysis that moves fluid- and neuro-dynamics problems toward actionable models.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at University of Washington
B.E. (Hons.) Mechanical Engineering, B.E. (Hons.) Mechanical Engineering at Birla Institute Of Technology and Science, Pilani Dubai