Levi Lelis’ research goal is to develop intelligent systems that are able to augment people through teaching and collaboration.

Intelligent systems, augmented strategies

Levi Lelis’ research goal is to develop intelligent systems that are able to augment people through teaching and collaboration. Currently, his group is working on algorithms to generate knowledge, such as strategies for playing games, that people can easily interpret and understand. They seek to use machine-generated knowledge to teach humans how to solve problems. For example, these machine-created interpretable strategies can be used to compile human-readable manuals for teaching people game strategies. Levi and his team are also investigating the use of interpretable machine-generated knowledge in human-machine collaborative tasks, where algorithms help humans to solve problems. In his current research, he and his group are seeking to advance the state of the art in heuristic search, machine learning, program synthesis, and explainable artificial intelligence.

Levi is a Fellow and Canada CIFAR AI Chair at Amii, an Assistant Professor in the Department of Computing Science at the University of Alberta and a Professor on leave from the Universidade Federal de Viçosa in Brazil. He received his Ph.D. in Computing Science in 2013 from the University of Alberta, studying under the supervision of Robert Holte (Amii Fellow and founding researcher) and Sandra Zilles. Levi has co-authored more than 45 refereed papers at venues such as the International Joint Conference on Artificial Intelligence (IJCAI), the conference for the Association for the Advancement of Artificial Intelligence (AAAI) and the Neural Information Processing Systems (NeurIPS) Conference. He has also served as a Senior Program Committee Member for IJCAI (where he received the honour of being the Distinguished Program Committee Member in 2018 and 2019) and AAAI and Program Committee Member for the Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE).