Aayushya Agarwal

Aayushya Agarwal is a Special Faculty member in the Department of Electrical and Computer Engineering at Carnegie Mellon University. His research focuses on developing computational design tools that tightly integrate artificial intelligence with physics-based optimization for next-generation large-scale, networked systems. His work targets high-impact applications including modernization of power grids, distributed AI training systems, circuit design, and advanced manufacturing. His work grounds AI and optimization in physical principles, enabling the use of circuit- and systems-level engineering design methodologies within modern numerical methods to build intuitive, robust, and scalable computational design tools.

Aayushya Agarwal is a researcher at Carnegie Mellon University focusing on optimization, power systems, and digital twin technologies. Their work addresses challenges in power flow optimization, security-constrained operations, and robustness in large-scale systems. Agarwal's research includes adversarial robustness techniques for stochastic optimal power flow, differential dynamic programming for multi-period optimization, and homotopy methods for AC-constrained optimal power flow. They also explore implicit control models, equivalent circuit workflows, and continuous switch models for mixed-integer nonlinear problems. Agarwal's contributions span both theoretical and applied aspects of power systems, with a focus on enhancing reliability, efficiency, and scalability in modern grid operations.