Sirui Liu

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About

Sirui Liu is a leading researcher in artificial intelligence and automated reasoning, with a focus on knowledge representation, logic programming, and combinatorial optimization. Their most notable contribution is the development of Answer Set Programming modulo Difference Constraints (ASP(DC)), a powerful framework that integrates temporal reasoning with declarative problem solving. Liu’s landmark 2023 paper, "Solving an Industrial-Scale Warehouse Delivery Problem with Answer Set Programming Modulo Difference Constraints," demonstrates the practical impact of this work by addressing a real-world logistics challenge: coordinating multiple robots to execute collision-free delivery schedules in dynamic warehouse environments. This approach has garnered 6 citations and is recognized for bridging the gap between theoretical logic programming and industrial-scale applications. Liu’s research is distinguished by its ability to model complex temporal and resource constraints, offering scalable solutions that have implications for robotics, supply chain management, and automated planning. By advancing ASP(DC), Liu has provided a robust tool for tackling NP-hard scheduling problems, earning a reputation for translating foundational AI research into deployable systems. Their work continues to inspire students and researchers in logic-based AI and operations research.