Short Bio
Pooyan Jamshidi is an Associate Professor in the Department of Computer Science and Engineering at the University of South Carolina, where he directs the Artificial Intelligence and Systems Laboratory. He received his Ph.D. in Computer Science from Dublin City University and completed postdoctoral research at Carnegie Mellon University and Imperial College London. He has also worked in industry, including as a Visiting Researcher at Google in 2021.
His research lies at the intersection of AI/ML, software systems, distributed systems, and robotics. His group develops methods for building resilient, adaptive, and efficient AI-enabled systems that operate under uncertainty, changing workloads, resource constraints, and real-world deployment conditions. His work combines causal inference, statistical learning, optimization, transfer learning, and systems design, with applications in ML systems, autonomous systems, performance engineering, edge/cloud intelligence, and hardware–software co-design. He received USC’s 2022 Breakthrough Stars Award, and two of his SEAMS papers received Most Influential Paper Awards.
Long Bio
Pooyan Jamshidi is an Associate Professor in the Department of Computer Science and Engineering at the University of South Carolina, where he directs the Artificial Intelligence and Systems Laboratory. Before joining USC, he was a postdoctoral researcher at Carnegie Mellon University from 2016 to 2018 and at Imperial College London from 2014 to 2016. He received his Ph.D. in Computer Science from Dublin City University in 2014 and his M.S. and B.S. degrees from Amirkabir University of Technology. He has also worked in industry, including as a Visiting Researcher at Google in 2021.
Pooyan’s research spans AI/ML systems, software systems, distributed systems, and robotics. His group develops algorithms, tools, and system abstractions that make complex AI-enabled systems more reliable, adaptive, efficient, and explainable when deployed in dynamic real-world environments. A central theme of his work is understanding and controlling how systems behave under changing workloads, configurations, resource constraints, user goals, and environmental conditions.
His research combines causal inference, statistical learning, optimization, transfer learning, representation learning, and systems design. These methods support performance debugging, configuration optimization, adaptive resource management, failure diagnosis, model and system co-design, and autonomous decision-making. His work has been applied to configurable software systems, cloud and edge systems, machine-learning inference pipelines, AI accelerators, autonomous robots, and embodied AI systems.
Pooyan is broadly interested in both ML for Systems and Systems for ML. His current research directions include efficient and trustworthy ML systems, agentic and embodied AI, robot learning, edge-to-cloud AI, resilient autonomy, sustainable AI, and hardware–software co-design for emerging AI workloads. He received USC’s 2022 Breakthrough Stars Award, and two of his papers at SEAMS received Most Influential Paper Awards for their sustained impact on self-adaptive systems research.
