New ISE assistant professors (L-R) Karmel S. Shehadeh, Shengbo Wang, Alfredo Torrico and Karthyek Murthy.
The Daniel J. Epstein Department of Industrial and Systems Engineering has welcomed four new faculty members for 2025, bolstering the department’s research strengths in areas spanning healthcare optimization, analytics, operations research and more.
These new faculty members bring diverse expertise, focusing on developing cutting-edge methodologies such as applied probability, stochastic optimization and game theory to solve complex, real-world problems across critical sectors including infrastructure, supply chains, transportation and healthcare.
Karthyek Murthy: Pioneering Data-Driven Decision-Making Under Uncertainty
Karthyek Murthy is an expert in risk analytics and operations research. He joins the Epstein Department as an assistant professor after his time at the Singapore University of Technology and Design, where he was an associate professor in the Engineering Systems and Design pillar.
Murthy develops quantitative models and algorithms that enable decisions despite uncertainty, with applications in areas such as traffic flow management, power distribution networks, and revenue management.
“My research focuses on developing a new generation of data-driven decision-making methods that tailor the use of modern machine learning tools towards producing decisions that are certifiably robust in their effectiveness and resilient to high-impact risk events,” Murthy said.
A lifelong lover of mathematics, Murthy said he is most excited by the opportunity his research area offers to improve lives and create real-world impact via mathematical models.
“I have always been fascinated by the philosophical aspects of how to grapple with the ‘known unknowns’, ‘unknown unknowns’, and what is intrinsically random,” Murthy said. “A question that has long fascinated me—and where we are now making significant progress—concerns how to provision high reliability in engineering systems, such as cloud service providers and power transmission networks, and the qualitative factors that influence the cost of achieving the levels of reliability required for critical infrastructures.”
Murthy has been honored with awards, including the 2024 INFORMS Simulation Society Publication Award and the IISE Modeling and Simulation Teaching Award. He is teaching ISE students in the Foundations of Stochastic Modeling class and said he is also looking forward to the opportunity to collaborate with the faculty in the Epstein Department and the broader Viterbi School.
Karmel S. Shehadeh: Advancing Robust and Fair Optimization for Healthcare, Transportation, and Logistics
Karmel S. Shehadeh is an expert in data-driven optimization under uncertainty and (mixed) integer programming. She joins the department as a WiSE Gabilan Assistant Professor of Industrial and Systems Engineering. Before joining USC, Shehadeh was an Assistant Professor of ISE at Lehigh University.
Shehadeh’s research program pushes the boundaries of the theory and applications of stochastic and distributionally robust optimization methodologies and their applications. Her research addresses challenging real-world problems across several application domains, including facility location, transportation systems, and healthcare operations and analytics. Most recently, Shehadeh has developed data-driven models to reduce delays in elective surgery and streamline hospital scheduling. Her upcoming project, “Advancing Contextual Stochastic Optimization via Distributionally Robust Optimization Techniques,” is supported by a grant from the Air Force Office of Scientific Research (AFOSR) under its Mathematical Optimization program.
“Another stream of my research focuses on fairness-promoting optimization, which is how to create mathematical optimization models that make fair decisions,” Shehadeh said.
Shehadeh is passionate about her research and its capacity to shape a future that is sustainable, fair and accessible.
“I’m really in love with research. For me, it’s like video games, in the way that you keep wanting to go to the next level, you want to address the next challenge,” she said. “I want to help the world, and that’s what draws me to addressing issues in healthcare, with all of its cost and resource constraints, and lack of accessibility.”
Shehadeh said that joining USC has been a “big dream” of hers, particularly given the Epstein Department’s diverse research areas and significant strengths in optimization, and the opportunities she will have to collaborate with colleagues at the Keck School of Medicine of USC, the METRANS Transportation Consortium, and the USC Center for Artificial Intelligence in Society (CAIS). Shehadeh is also looking forward to contributing to USC Viterbi’s K-12 STEM outreach programs and will be teaching students in the ISE 530 Optimization Methods for Analytics class.
“I love teaching and I’m looking forward to teaching the next generation here at USC,” she said.
Alfredo Torrico: Bridging Theory and Practice in Urban and Societal Systems
Alfredo Torrico is an assistant professor who joins the Epstein Department from Cornell University, where he served as an assistant research professor in the Center for Data Science for Enterprise and Society.
Torrico’s research agenda aims to bridge theory and practice by employing applied modeling and methodological tools from optimization, game theory, and algorithm design to analyze challenges faced by public and private services in urban centers. His work focuses on understanding the trade-offs that appear when different, and often conflicting necessities—such as efficiency, welfare, and revenue—are considered in high-stakes settings.
“Some examples of my recent works include analyzing different pricing schemes to address traffic congestion in cities such as New York and Bogota, using optimization tools to address overcrowded school districts, and developing tools to improve the efficiency of choice-based matching platforms such as dating, freelancing and lodging apps like Bumble, Upwork and Airbnb,” Torrico said.
Torrico is excited by the combination of theoretical and practical aspects of Operations Research and is particularly interested in the kind of research questions that would help policymakers and organizations make well-informed decisions.
Torrico said he is looking forward to collaborating with faculty and students in the Epstein department, but also beyond with faculty in computer science, operations management and economics.
“Addressing societal and business needs requires an interdisciplinary approach, and USC is the perfect place for that,” Torrico said.
Shengbo Wang: Dynamic Decision-Making and Robust Policy Learning
Shengbo Wang joins the Epstein Department as an assistant professor, bringing expertise in a wide range of areas within applied probability, machine learning, and simulation. He received his Ph.D. from the Department of Management Science and Engineering (MS&E) at Stanford University.
Wang’s research focuses on the design and analysis of algorithms for learning and controlling dynamic engineering systems, with applications in management science and operations research. A key area of his research is the development of statistically tractable data-driven models and algorithms for robust dynamic policy learning and Reinforcement Learning (RL).
“A central theme of my work is robust policy learning,” Wang said. “As modern environments are increasingly non-stationary and confounded, with new algorithms deployed rapidly across multiple sectors of the economy, systems must be able to anticipate and adapt to environmental shifts to mitigate cascading risks.”
Wang became interested in robustness during the COVID-19 pandemic, when massive supply chain disruptions revealed system vulnerabilities. “This drew me to robustness as a research theme where practical urgency and mathematical depth intersect, and it is precisely this intersection that makes me most excited about the work I do,” he said.
Wang said he is particularly excited about the opportunity to broaden his perspective on optimization and collaborate with faculty in the Epstein Department who are exceptionally strong in this area.
“At the same time, I am enthusiastic about contributing to the department’s teaching mission by offering courses on reinforcement learning, statistics, and stochastic processes,” Wang said. “At both the undergraduate and graduate level, I aim to give students fresh perspectives on dynamic decision-making problems, equipping them to tackle the challenges and opportunities of modern data-driven systems.”
Published on October 30th, 2025
Last updated on October 30th, 2025
