Master Class

Malte Helmert is a professor for computer science at the University of Basel. His main research interests are in classical planning and heuristic search, with an emphasis on domain-independent algorithms for synthesizing distance heuristics in factored state spaces. His research group at the University of Basel leads the development of the Fast Downward planning system.

Florian Pommerening is a postdoctoral researcher in the AI group at the University of Basel, Switzerland, where he completed his PhD from 2012 to 2017. His main research interest is classical automated planning. In his PhD thesis, he used linear and mixed integer programs to automatically derive heuristic functions. His research in the area received best paper awards from ICAPS 2014, AAAI 2015, and ICAPS 2019.

Scott Sanner is a Professor in Industrial Engineering and Cross-appointed in Computer Science at the University of Toronto. He was a Visiting Researcher at Google (UK) while on sabbatical (2022-23).  His research focuses on a broad range of AI topics spanning sequential decision-making, (conversational) recommender systems, and applications of machine/deep learning.  Scott is currently an Associate Editor for ACM Transactions on Recommender Systems (TORS) and the Machine Learning Journal (MLJ) and Chair of the Editorial Board for the Journal of AI Research (JAIR). Scott was a co-recipient of paper awards from AI Journal (2014), Transport Research Board (2016), and CPAIOR (2018).

Edward Lam is a Research Fellow in the Department of Data Science & Artificial Intelligence at Monash University, where he develops algorithms and solvers for combinatorial optimization, with applications to large-scale operations planning problems in logistics, transportation and warehousing. His research integrates integer programming, constraint programming, and heuristic search via decomposition methods to solve larger problems faster than standard approaches, with several of his solvers achieving world-leading performance on benchmark problems.