If you are interested to work with me on exciting research projects in decision making under uncertainty, robot motion planning, reinforcement learning, with applications on robotics, please drop me an e-mail or stop by my office. I have openings for Postdoctoral Research Fellow, PhD, and Research Assistant positions.
Short biography
Hanna Kurniawati is a Professor in the School of Computing and holds the SmartSat CRC Professorial Chair for System Autonomy, Intelligence & Decision-Making. She leads the Robust Decision-making and Learning Lab at the ANU and is the ANU Node Lead and Planning & Control Theme Lead for the Australian Robotics Inspection and Asset Management (ARIAM) Hub. Hanna’s research spans robotics, decision-making under uncertainty, motion planning, computational geometry applications, integrated planning and learning, and reinforcement learning. She and her teams have developed algorithms that enable the principled decision-making under uncertainty framework to become practical. Hanna’s works have received multiple recognitions, including Best Paper at ICAPS 2015, finalist for Best Paper at ICRA 2015, keynote speaker at IROS 2018, and the Robotics: Science and Systems 2021 Test of Time Award.
More info about Hanna’s research is here.
A bit more about me
I am a Professor at the School of Computing, Australian National Univeristy (ANU), and the SmartSat CRC Professorial Chair for System Autonomy, Intelligence, and Decision Making. I am the ANU Node Lead and the Planning & Control theme lead for the Australian Robotics Inspection and Asset Management (ARIAM) Hub. At ANU, I founded the Robot Decision Making group and was a deputy lead of the interdisciplinary research project Humanising Machine Intelligence. I earned a BSc in Computer Science from the University of Indonesia and a PhD in Computer Science for work in Robot Motion Planning from National University of Singapore. After my PhD, I worked as a Postdoctoral Associate, and then a Research Scientist at the Singapore-MIT Alliance for Research and Technology, MIT. I was a faculty member at the University of Queensland School of ITEE and moved to ANU in 2019, as an ANU and CS Futures Fellow.
My research interests span planning under uncertainty, robotics, robot motion planning, integrated planning and learning, and computational geometry applications. Specifically, I focus on algorithms to enable robust decision theory to become practical software tools, with applications in robotics and the assurance of autonomous systems. Specifically, together with collaborators and students, I have developed algorithms that enable the principled decision-making under uncertainty framework, namely the Partially Observable Markov Decision Process (POMDP) –deemed computationally intractable for over 40 years– to become practical for robotics, at least to some extent. Such software tools will enable robots to design their own strategies, such as deciding what data to use, how to gather the data, and how to move, for accomplishing various tasks well, despite various modelling errors and types of uncertainty, and despite limited to no information about the system and its operating environment.
Together with collaborators and students, my work has received multiple recognitions, including a best paper award at the International Conference on Automated Planning and Scheduling (ICAPS) 2015, nomination for the best paper award at IEEE Int. Conf. on Robotics and Automation (ICRA) 2015, a gold award for ICT researcher of the year 2015 from the Australian Computer Society, a keynote talk at IEEE/RSJ Int. Conf. on Intelligent Robots (IROS) 2018, and the Robotics: Science and Systems 2021 Test of Time Award.
I am actively involved in the robotics community, including as a Senior Editor for IEEE RA-L, General Chair for SIMPAR’18, and Program Co-Chair for ICRA’22.