USC Helps Lead $20 Million NSF Push to Fuse AI and Optimization for Resilient Power Grids and Supply Chains

The University of Southern California is set to play a leading role in one of the most ambitious applied artificial intelligence efforts in the United States, after the U.S. National Science Foundation awarded $20 million to renew the Artificial Intelligence Institute for Advances in Optimization, known as AI4OPT, through 2031. The institute, led by the Georgia Institute of Technology in partnership with USC and the University of California, Berkeley, sits at the intersection of two disciplines that are rapidly reshaping how modern infrastructure is managed: machine learning and mathematical optimization. Its central premise is that neither field alone can solve the decision-making problems posed by increasingly complex power grids, manufacturing systems and global supply chains, but that their combination can.

Optimization, in the technical sense, is the science of finding the best possible course of action when time, money, energy, materials or other resources are constrained. It underpins how airlines schedule crews, how utilities dispatch electricity, how warehouses route packages and how factories sequence production lines. Traditionally, these problems have been tackled with exact mathematical programming techniques such as linear, integer and mixed-integer programming, which can guarantee optimal solutions but often struggle when problems grow to enormous scale or when the underlying conditions are uncertain and fast-changing. AI4OPT was created to close that gap by teaching machines to solve such problems more efficiently, blending learning-based approaches with classical algorithmic methods.

The stakes are rising because the systems being optimized are themselves becoming more complicated and less predictable. Power grids that once relied on a manageable number of large, dispatchable generators must now integrate variable renewable sources, distributed storage, electric vehicle charging and fluctuating demand, all while operators respond faster than traditional planning cycles allow. Supply chains that span continents face shortages, geopolitical disruptions and shifting consumer patterns that can invalidate carefully built plans within hours. Manufacturing systems increasingly need to adapt production in near real time. In each case, the challenge is not simply computing a good plan once, but continuously recomputing and revising decisions as conditions change, under uncertainty and at scales that overwhelm conventional methods.

AI4OPT’s response is to develop intelligent systems capable of navigating that uncertainty, making complex decisions and responding quickly as conditions evolve. The researchers aim to explore how AI and optimization can work together to achieve advances that neither field could deliver on its own, and then to move those advances out of foundational research and into large-scale applications. In practice, this can mean using machine learning to guide the search of optimization solvers toward promising regions of an otherwise intractable solution space, using learned models to predict the uncertain inputs that an optimization model must account for, or embedding optimization layers inside learning systems so that the resulting decisions respect real-world physical and operational constraints.

At USC, the effort will be co-led by Bistra Dilkina, co-principal investigator of AI4OPT and the Dr. Allen and Charlotte Ginsburg Early Career Chair in Computer Science and associate professor of computer science at the USC Viterbi School of Engineering. Dilkina’s research focuses on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly those arising in sustainability domains such as biodiversity conservation planning and urban planning. That background in applying rigorous optimization to consequential societal problems mirrors the institute’s broader mission of translating basic science into tools with tangible impact.

“This renewal allows us to dig deeper into AI and optimization, moving basic science toward real-world applications that make a tangible difference in society,” Dilkina said. Her counterpart at the helm of the institute is Pascal Van Hentenryck, the A. Russell Chandler III Chair and professor at Georgia Tech, who will continue to serve as lead principal investigator. Alper Atamtürk of UC Berkeley joins as the third co-principal investigator, giving the renewed institute leadership distributed across three of the country’s leading research universities. “By fusing AI and optimization, AI4OPT is changing how we solve energy, supply chain and manufacturing challenges that are at the core of society,” Van Hentenryck said.

The renewal represents a substantial escalation of USC’s involvement. The university will receive $5.6 million, more than twice its funding during the institute’s first phase, and will expand its research team from two researchers to five. The new interdisciplinary team draws faculty from across USC Viterbi, the USC Mark and Mary Stevens School of Computing and Artificial Intelligence, and the USC Marshall School of Business, reflecting the fact that the problems AI4OPT targets are simultaneously technical, computational and economic. “With an expanded team and increased support, USC is excited to collaborate with our partners to push boundaries and amplify our collective strengths,” said Dilkina, who also co-directs the USC Center for AI in Society.

The potential applications span the critical infrastructure that modern society depends on. For utilities, intelligent optimization systems could help balance increasingly complex power grids, coordinating generation, storage and demand in ways that maintain reliability while accommodating clean energy resources whose output changes with weather and time of day. For manufacturers, the same underlying methods could adjust production schedules dynamically as materials, orders and machine availability shift. For supply chain operators, the tools could support rapid responses to shortages and disruptions, rerouting goods and reallocating inventory before small disturbances cascade into systemic failures. What unites these domains is the structure of the underlying problem: enormous numbers of interdependent decisions, hard constraints, uncertain and changing conditions, and severe penalties for slow or poor choices.

Beyond the research itself, the renewed institute places heavy emphasis on education, with initiatives that stretch from high school classrooms to doctoral training. As part of the renewal, USC will bring the Seth Bonder summer camp in computational and data science for engineering to high school students in Los Angeles, extending hands-on exposure to data-driven engineering methods to a new audience. At the graduate level, the institute’s presence at USC has already helped catalyze the university’s leadership in AI and optimization education, including the launch of the first PhD specialization and certificate in AI plus optimization, known as USC’s ORAI program, supported by a National Science Foundation Research Traineeship grant. Together, these efforts are designed to create educational pathways for students at different stages to build skills in AI, optimization and their real-world applications, addressing a persistent shortage of researchers who are fluent in both machine learning and mathematical decision science.

The five-year renewal through 2031 signals a long-horizon commitment to a research agenda that many experts consider essential for the energy transition and the resilience of global commerce. As AI systems move from generating text and images to making consequential operational decisions, the ability to guarantee that those decisions are feasible, efficient and robust becomes paramount. AI4OPT’s bet is that the fusion of learning and optimization is the key to that guarantee, and that the resulting methods will determine how well power grids, factories and supply chains absorb the shocks of a rapidly changing world. With USC’s expanded role, one of the country’s largest urban research universities is now positioned to shape both the science of that fusion and the workforce trained to deploy it.

Subject of Research: AI-driven optimization for power grid, manufacturing and supply chain decision-making

Article Title: USC joins $20M NSF effort to transform power grids and supply chains

Article References: USC joins $20M NSF effort to transform power grids and supply chains. (n.d.). Original publication

Image Credits: AI Generated

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Keywords: artificial intelligence, optimization, power grids, supply chains, manufacturing, NSF, AI4OPT, USC, Georgia Tech, machine learning, combinatorial optimization, STEM education