• E. Liebman, C.N. White & Peter Stone, "On the Impact of Music on Decision Making in Cooperative Tasks", 19th International Society for Music Information Retrieval Conference (ISMIR 2018), September 2018 (acceptance rate 40%)
• E. Liebman, E. Zavesky & P. Stone, "A Stitch in Time: Autonomous Model Management via Reinforcement Learning", 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018) July 2018 (accetpance rate 25%)
• E. Liebman, P. Khandelwal, M. Saar-Tsechansky & P. Stone, "Designing Better Playlists with Monte-Carlo Tree Search", 29th Conference on Innovative Applications of Artificial Intelligence (IAAI-17, co-located with AAAI-17), February 2017 (accetpance rate 37%)
• E. Liebman, P. Stone & C.N. White, "Impact of Music Stimuli on Decision Making in Quantitative Tasks", 17th International Society for Music Information retrieval Conference (ISMIR), August 2016 (acceptance rate 47%)
• P. Khandelwal, E. Liebman, S. Niekum & P. Stone, "On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search ", 33rd International Conference on Machine Learning (ICML), June 2016 (acceptance rate 24%)
• E. Liebman, P. Stone & C. N. White, "How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification", 16th International Society for Music Information retrieval Conference (ISMIR), October 2015 (acceptance rate 44%, accepted for oral presentation)
• E. Liebman, M. Saar-Tsechansky & P. Stone, "DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation", 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015 (acceptance rate 24%)

• E. Liebman, M. Saar-Tsechansky and P. Stone, "The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling", Management Information Systems Quarterly (MISQ), accepted - forthcoming.
• C. N. White, E. Liebman, P. Stone, "Decision mechanisms underlying mood-congruent emotional classification", Cognition and Emotion, March 2017
• E. Liebman, B. Chor & P. Stone, "Representative Selection in Non Metric Datasets", Applied Artificial Intelligence, September 2015
• A. Wagner, N. Cohen, T. Kelder, U. Amit, E. Liebman, D. M. Steinberg, M. Radonjic and E. Ruppin, Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia, Molecular Systems Biology, March 2015
• E. Liebman, E. Ornoy & B. Chor, "A Phylogenetic Approach to Music Performance Analysis", Journal of New Music Research, June 2012

• Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone, "Fast and Precise Black and White Ball Detection for RoboCup Soccer", RoboCup-2017 symposium, July 2017
• E. Liebman, E. Zavesky & P. Stone, "Autonomous Model Management via Reinforcement Learning - Extended Abstract", 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017) May 2017 (extended abstract)
• P. MacAlpine, E. Liebman & P. Stone, "Adaptation of Surrogate Tasks for Bipedal Walk Optimization", GECCO Surrogate-Assisted Optimization (SAE-Opt) Workshop, July 2016
• E. Liebman, P. Stone and C. N. White, "Decision Mechanisms Underlying Mood-Congruent Emotional Classification", 2nd Conference on Reinforcement Learning and Decision Making (RLDM), June 2015
• E. Liebman, "Intelligent Learning Agents for Music-Based Interaction and Analysis", AAMAS Doctoral Consortium, May 2015
• E. Liebman & P. Stone, "DJ-MC: A Reinforcement-Learning Framework for a Music Playlist Recommender System", 1st Conference on Reinforcement Learning and Decision Making (RLDM), October 2013
• P. MacAlpine, E. Liebman & P. Stone, "Simultaneous Learning and Reshaping of an Approximated Optimization Task", AAMAS Autonomous Learning Agents (ALA) Workshop, May 2013

• K. Iwata, E. Liebman, P. Stone, T. Nakashima, Y. Anan and N. Ishii, "Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines", in "Computer and Information Science 2015", Studies in Computational Intelligence vol. 614, Springer International Publishing.

• K. Genter, P. MacAlpine, J. Menashe, J. Hannah, E. Liebman, S. Narvekar, R. Zhang, and P. Stone, "UT Austin Villa: Project-Driven Research in AI and Robotics", IEEE Intelligent Systems, Expert Opinion, March 2016

• Talk, "Intelligent Learning Agents for Music-Based Interaction and Analysis", invited talk, IBM Research, 2016
• Talk, "DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation", The 13th Bar-Ilan Symposium on the Foundations of Artificial Intelligence, 2015
• Talk, "A Phylogenetic Approach to Music Performance Analysis", CMPCP Performance Studies Network, Third International Conference, 2014
• Poster Presentation, "A Phylogenetic Approach to Music Performance Analysis", The 14th Israeli Bioinformatics Symposium, 2012
• Talk, "Bioinformatic Approaches to Music Analysis", Seventh Edmond J. Safra Bioinformatics Retreat, 2012
• Poster presentation, "A Phylogenetic Approach to Music Performance Analysis", Sixth Edmond J. Safra Bioinformatics Retreat, 2011
• Poster presentation, "Algorithmic Approaches to Deciphering the Geneaology of Music Performances",The Computer Science Department Competition for Exceptional Projects, Tel Aviv University, 2009