Elad Liebman
Ph.D. Student
Elad is interested in machine learning and its application in autonomous multiagent settings, as well as the emergent field of computational musicology. Before coming to UT he did his undergrad in CS and music composition (double-major program) and a MSc in CS, both at Tel Aviv University (his Masters thesis subject: A Phylogenetic Approach to Music Performance Analysis). Elad's current work focuses on learning musical preferences and modeling the effect of musical stimuli on human decision making. In his free time, Elad enjoys music in every way and form (listening to it, playing the piano and the guitar, and writing his own), reading (anything from classic literature and philosophy to the sports section), cooking, and playing racquetball.
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation 2015
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone, In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Simultaneous Learning and Reshaping of an Approximated Optimization Task 2013
Patrick MacAlpine, Elad Liebman, and Peter Stone, In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
Currently affiliated with Learning Agents