Adrian Pearce is a Professor and Deputy Head of School (Engagement) in the School of Computing and Information Systems within the Faculty of Engineering and Information Technology at the University of Melbourne. He earned a BSc with first-class Honours in Computer Science from the University of Melbourne and a PhD in Computer Science from Curtin University, Perth, under the APAI Award. After completing a Postdoctoral Research Fellowship, he served as a Lecturer at Curtin University before joining the University of Melbourne in 2000, advancing through the ranks to his current position. Previously, he directed the Defence Science Institute for nine years until 2024.

Pearce conducts research in automated planning and scheduling, focusing on reasoning about action and change through situation calculus, classical planning, generalized planning, and reinforcement learning. His interests include strategy synthesis using game structures and linear temporal logic, introspective reasoning with theory of mind via epistemic logic and nested beliefs, contextual reasoning and ontology adaptation employing intuitionistic logic and higher-order type theory, and discrete and continuous optimization via mathematical programming methods such as dual decomposition, mixed-integer programming, and SAT solving. Applications span production scheduling, cognitive robotics, multi-agent systems, supply chain logistics, and autonomous decision-making. He has supervised over 15 PhD candidates, many now at organizations like Google, Meta, and Mozilla. Pearce received the Outstanding (Best Paper) Award at the International Conference on Automated Planning and Scheduling in 2015 and the Erasmus Mundus Academic Scholar Award in 2014. He held visiting academic positions at the Free University of Bozen-Bolzano in 2014 and Sapienza University of Rome in 2009 and 2014. As a senior program committee member and chair for conferences including IJCAI, AAAI, ICAPS, KR, and AAMAS, he has shaped AI planning advancements. Key publications include "ROADMAP: extending the Gaia methodology for complex open systems" (2002), "Short-term planning for open pit mines: a review" (2019), "Planning over multi-agent epistemic states: A classical planning approach" (2015), "A decomposition-based algorithm for the scheduling of open-pit networks over multiple time periods" (2016), and "Efficient multi-agent epistemic planning: Teaching planners about nested belief" (2022). He is a member of AAAI, ACM, IEEE, and Senior Member of the Australian Computer Society.

Professional Email: adrianrp@unimelb.edu.au