Felipe Werndl Trevizan

Felipe Werndl Trevizan is a Senior Lecturer in the School of Computing at the Australian National University (ANU), where he conducts research at the intersection of Artificial Intelligence, Operations Research, and Machine Learning. His work focuses on automated planning and scheduling, reasoning under uncertainty, heuristic search, and machine learning for planning. He is actively involved in research projects related to uncertainty-centric pilot assistance systems and probabilistic planning.

His research interests include:

• Automated Planning and Scheduling
• Probabilistic and Multi-Objective Planning
• Heuristic Search and Admissible Heuristics
• Deep Learning for Generalized Planning
• Constraint-Based and Risk-Aware Planning
• Learning Heuristics from Data

His recent publications demonstrate a strong trend toward integrating machine learning with classical planning techniques, particularly in learning reliable, domain-independent heuristics using both deep and classical machine learning methods. He has developed novel algorithms for constrained and stochastic shortest path problems, multi-objective probabilistic planning, and generalized planning using neural networks.

His scientific awards include:

• Best Paper Award at ICAPS 2016
• Best Paper Award at ICAPS 2017
• 2016 Kikuchi-Karlaftis Best Paper Award from the Transport Research Board

Felipe Werndl Trevizan is registered to supervise research students and has advised several successful projects in AI planning. He has secured research grants for projects such as 'Integrated Planning for Uncertainty-Centric Pilot Assistance Systems' and 'Chance-Constrained POMDP for Pilot Assistance Systems' at ANU. He is also organizing key community events including the 'Reliability In Planning and Learning (RIPL)' workshop and a tutorial on 'Learning for Planning' at ICAPS 2025.

He is affiliated with the School of Computing at ANU and previously worked as a Senior Research Scientist at NICTA and Data61/CSIRO. His research is supported by active collaborations with leading researchers such as Sylvie Thiébaux, Hanna Kurniawati, and others.