Andrew Chio: Building Resilient Systems for Critical Infrastructures: A Model-Driven and Data-Driven Approach

Title:

Building Resilient Systems for Critical Infrastructures: A Model-Driven and Data-Driven Approach

Abstract:
Critical infrastructures such as water, power, and buildings are large-scale distributed systems that serve as essential lifelines for communities worldwide. Today, they face unprecedented resilience challenges affecting millions of people and cause billions in damage. In this talk, I will present my research addressing fundamental computational challenges in these cyber-physical systems by combining model-driven approaches that encode physics and network constraints with data-driven techniques that learn from real-world patterns. I will demonstrate this across three critical infrastructure domains, addressing key resilience challenges. First, I present STEP, a framework that solves the NP-hard sensor placement problem for detecting transient contamination events in stormwater networks. Second, I introduce SEQUIN, which leverages network science principles and physics-based optimization to identify sequential attack patterns. Third, I showcase SmartSPEC, an event-driven simulation framework that generates realistic synthetic human behavioral data by exploiting environmental semantics. Together, these systems demonstrate how integrating models and data can address diverse resilience challenges for societal-scale systems.

Bio:
Andrew is a final PhD candidate in the Distributed Systems Middleware (DSM) Group at the University of California, Irvine, advised by Prof. Nalini Venkatasubramanian. He is also affiliated with the Los Alamos National Laboratory, working with Dr. Russell Bent in the T-5 Theoretical Division Applied Mathematics and Plasma Physics Group. His research interests lie at the intersection of cyber-physical systems, optimization, middleware, and artificial intelligence. His current work focuses on building systems that enhance the resilience of societal-scale cyber-physical systems such as electric power grids, stormwater networks, and smart buildings. His work has been published in top venues such as ACM/IEEE ICCPS, IEEE PerCom, ACM BuildSys, and VLDB. He is the recipient of the NSF CPS Rising Stars Award in 2025, the CPS-Week PhD Forum Best Poster Award in 2025, the UC National Lab In-Residence Graduate Fellowship in 2022, the ARCS Foundation Scholarship in 2022, as well as the Best Paper Award in IEEE PerCom 2022.