Sai Krishna Kanth Hari
Los Alamos National Laboratory
Biography
Research scientist with interests in critical infrastructure network planning, autonomous vehicle planning and applied optimization. Background in civil and mechanical engineering.
SRP Project Title
Scalable Algorithms for Critical Infrastructure Network Planning
Topical Areas
Applied Computer Science; Applied Mathematics; Artificial Intelligence and Intelligent Systems; Chemical Engineering; Civil Engineering; Computer Science; Electrical, Electronic, and Information Engineering; High Performance Computing; Hydrology and Water Resources; Infrastructure and Instrumentation; Mechanical Engineering
Abstract
Critical infrastructure networks—such as power grids, water distribution systems, and natural gas pipelines—form the backbone of modern society. Planning their design, daily operation, and expansion requires repeatedly solving large-scale, complex optimization problems. These problems are computationally challenging due to nonlinear and nonconvex flow models, discrete decision variables, and the vast scale of network systems. This project focuses on developing scalable optimization algorithms for such critical infrastructure systems. We leverage techniques such as linear relaxations, spatial and temporal decomposition, and problem-structure exploitation to design methods capable of handling realistic, high-fidelity flow models efficiently. The outcomes aim to enable faster and more reliable decision-making in infrastructure planning and operation—directly supporting the Department of Energy’s mission to enhance the resilience, efficiency, and security of national energy and water networks.
Desired Skills
Interest in optimization algorithms, energy or network systems, or applied mathematics; experience with Julia, Python, C++, or MATLAB.
Lightning Talk Title
Scalable Algorithms for Critical Infrastructure Network Planning
Keywords
Optimization, critical infrastructure, energy systems, network modeling, algorithms, decomposition, applied mathematics, computational methods.