Hanna Kurniawati

  • Theme Lead - Planning and Control (ANU Node Lead)
  • Professor
  • Institution: Australian National University (ANU)
  • Twitter: -
  • LinkedIn: -

Bio: Hanna Kurniawati is a Professor with ANU Futures Fellowship at the Australian National University (ANU). She leads the Robust Decision-Making and Learning Lab, part of the Planning and Optimisation group at the ANU School of Computing. She is also a deputy lead for the ANU Humanising Machine Intelligence Grand Challenge Project.

Hanna receives a PhD for work on high dimensional motion planning from the National University of Singapore. Before joining the ANU, Hanna was a faculty member at the University of Queensland. From 2013 to 2020, she was also a Research Affiliate at the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT). In 2019, Hanna received an ANU Futures Fellowship –a highly competitive fellowship to attract and retain world-leading early and mid-career researchers at the ANU.

Research Expertise:

Hanna’s research focuses on robust decision-making and motion planning under uncertainty. Her fundamental research has received multiple awards, including the Robotics: Science and Systems 2021 Test of Time Award for pioneering work on robust planning in the non-deterministic and partially observable world.

In addition to fundamental research, Hanna is leading collaborative projects with several industry partners on the applications of planning under uncertainty in robotics and related domain, such as AI-based co-pilot for Helicopter Emergency Medical Services.

In this hub, Hanna will lead the planning and control theme. She is particularly interested in investigating highly scalable and adaptable planning and learning under uncertainty approaches. Such approaches would enable robots to accomplish inspection and intervention tasks safely and robustly, despite substantial uncertainty, including partial observability, non-deterministic effects of actions, information gaps, limited data, and changing and unpredictable nature of the operating environments.

View all profiles