Bar-Ilan University



Bar-Ilan University, founded in 1955, is one of Israel’s leading institutions of higher education, uniquely combining cutting-ege scientific research with education steeped in Jewish values and social responsibility.  From 70 students to close to 19,000, its milestone achievements in the sciences and humanities and all fields of human endeavor have made an indelible imprint on the landscape of the State of Israel.  The university has 8 faculties: Jewish Studies, Medicine, Engineering, Law, Life Science, Exact Sciences, Social Sciences, and Humanities.  These faculties are active partners in Israel’s national science and technology initiatives.

AI Labs

Prof. Kraus’ Lab
Prof. Sarit Kraus of the Department of Computer Science and the Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center is best known for her pioneering work in imparting intelligence upon computerized agents.  Kraus introduced the aspect of individualism to the field of multiple agent systems by developing protocols and strategies for individual agents that need to collaborate with each other.
Prof. Aumann’s Lab
Prof. Yonatan Aumann is a Professor in the Department of Computer Science. Aumann and his team conduct research that spans many subjects within the general field of the theory of computing, including parallel and distributed algorithms, cryptography, approximation algorithms, pattern matching, parametrized complexity and more. In addition, Aumann and team consider applications of the theory to more practical domains, including artificial intelligence, social choice and interaction, and computational biology.
MAVERICK Robotics & Artificial Intelligence Lab
The MAVERICK research group conducts research at the absolute cutting edge of artificial intelligence and robotics. We are interested in both mechanisms (algorithms that do one thing well), as well as in architectures (systems that integrate mechanisms, to do many things well). Broadly speaking, we are interested in how to build artificial social minds. This translates into specific interests and research projects combining planning, execution, and machine learning in areas such as multi-robot coordination and teamwork, robot swarms (including molecular robots (nanobots)), plan recognition, behavior recognition, and goal recognition. Sometimes, the research takes us further than anticipated, e.g., our work on nanobots has produced the Rivendell meta-search engine for research papers, and our interest in plan recognition has led to investigate models human social cognition. Our work on teamwork in multi-robot systems have led to new algorithms for robot coverage path planning, for multi-robot formation maintenance, robot patrolling and other multi-robot tasks.
Prof. Koppel’s Lab
Prof. Moshe Koppel of the Department of Computer Science conducts research on a variety of machine learning applications including text categorization, image processing, speaker recognition and automated game playing. He is best known for his contributions to the branch of text categorization concerned with authorship attribution. More recently, he has begun researching fundamental problems in social choice theory.
Prof. Ido Dagan’s Natural Language Processing (NLP) Lab
Research at Prof. Ido Dagan’s Natural Language Processing (NLP) Lab in the Department of Computer Science is dedicated to applied semantic processing. For over a decade, Dagan’s work has focused on empirical and learning methods for language processing, with a particular emphasis on unsupervised semantic learning. In the last several years, he and his team introduced textual entailment as a generic framework for applied semantic inference over texts. This framework aims to power the core semantic inferences in many NLP applications. With other colleagues, they organized the seven rounds of the PASCAL Recognizing Textual Entailment (RTE) Challenges (2005-2011), which became the primary forum for empirical evaluation of semantic inference systems. These challenges were adopted as a track at the Text Analysis Conference (TAC), the primary evaluation forum for semantic text processing organized by the U.S. National Institute of Standards and Technology (NIST). At Bar-Ilan, Dagan’s NLP group develops computational models of textual entailment, including automatic knowledge acquisition, semantic inference, and information access applications, as detailed below. Dagan was awarded the Wolf Foundation Krill Prize for Excellence in Scientific Research in 2008 in recognition of his contributions to the field, and the IBM Faculty Award in 2007. He was elected as the President of the Association for Computational Linguistics (ACL) for 2010, and has been serving on its Executive Committee during 2008-2011.

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