Since October 2017 I am a Senior Lecturer at the Australian National University. From June 2015 I was a founder at HIVERY, and in 2017 also a Catalyst in Residence at the Michael Crouch Innovation Centre at the Univeristy of New South Wales. Working with industry, I developed data-driven systems that optimize by creating retail-AI technologies which coupled industrial optimisation with machine learning. From August of 2011 I was at the NICTA (then Data61) lab and part of CECS at ANU in Canberra. I was working at the intersection of Artificial Intelligence and Operations Research on solutions to fleet logistics problems. Before that I was a research fellow with the Intelligent Robotics Lab at the University of Birmingham 2008-2011; There I worked on a project investigating cognitive robots that can self-understand and self-extend. I was a researcher with the NICTA lab in Brisbane 2006-2008; There, I worked on fundamental research in AI Search, and simulation studies of city wide evacuation planning. I am the primary author of NMRDPP, runner up in the probabilistic track of the 2004 International Planning Competition. Co-author of ayPlanAgain, runner up in the multi-core track of the 2011 International Planning Competition. Co-author of best paper at the 2010 Pacific Rim International Conference on Artificial Intelligence. Co-author of gNovelty+, winner of the "Random" category at the 2007 International SAT competition.
I am a computer scientist who works in a sub-field of Artificial Intelligence called Automated Planning. Although my interests extend to other subjects in Machine Learning and Automated Reasoning, my expertise lies mostly within planning. My goal is to study and develop planning technology that will allow machines (i.e., robots and computers) to reason about deliberations in their world, and to reason about how to extend their own model of the world intelligently. Specialties: decision-theoretic planning, non-Markovian rewards, probabilistic planning, relational reinforcement learning, SAT-based deterministic/classical and probabilistic planning.