Robert Frank (Yale University)

Details: To be given

Robert Frank is Professor of Linguistics at Yale University. He received his PhD from the University of Pennsylvania (Computer and Information Science) and has taught at Johns Hopkins University (Cognitive Science) and the University of Delaware (Linguistics). His research explores models of language learning and processing and the role of computationally constrained grammar formalisms, especially Tree Adjoining Grammar, in linguistic explanation.

Gail Weiss (Technion)

Details: To be given

Gail Weiss is a PhD student at the Technion in Israel, working with professors Eran Yahav and Yoav Goldberg. She completed her BSc in Computer Engineering at the Technion in 2016 summa cum laude. Her research focuses on the application of formal language theory to deep learning techniques, particularly those used in NLP.

Invited Speakers

Dana Fisman (Ben-Gurion University)

Details: To be given

Dana Fisman is a faculty member in the Computer Science Department at Ben-Gurion University. Before that she was a research scientist at the University of Pennsylvania, the Associate Director of the NSF expedition ExCAPE about system synthesis, and a visiting fellow at Yale University. She did her PhD in Weizmann Institute of Science, and worked many years in the industry in IBM Haifa Research Labs, and in Synopsys Inc. Dana’s research interests are in the area of formal methods in system design, automata and logic. She is mostly known for her work on PSL, the IEEE standard for property specification language, on which she received numerous awards from IEEE, IBM and Synopsys.

Guillaume Rabusseau (Université de Montréal)

Details: To be given

Guillaume Rabusseau is an Assistant Professor at Mila and in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal, and a Canada CIFAR AI Chair holder. His research interests lie at the intersection of theoretical computer science and machine learning, and his work revolves around exploring inter-connections between tensors and machine learning and developing efficient learning methods for structured data relying on linear and multilinear algebra. In particular, in the field of grammatical inference, his work builds upon the so-called spectral learning algorithm for weighted automata over strings and trees. Prior to joining Mila, Guillaume Rabusseau was an IVADO postdoctoral research fellow in the Reasoning and Learning Lab at McGill University, and obtained his PhD in computer science in 2016 at Aix-Marseille University under the supervision of François Denis and Hachem Kadri.

C. Lee Giles (Pennsylvania State University)

Details: To be given

Dr. C. Lee Giles is the David Reese Professor at the College of Information Sciences and Technology at the Pennsylvania State University, University Park, PA. He is also graduate college Professor of Computer Science and Engineering, courtesy Professor of Supply Chain and Information Systems, and Director of the Intelligent Systems Research Laboratory.  He recently became a Teaching and Learning Technology Fellow and the Interim Associate Dean of Research for IST. He directs the Next Generation CiteSeer, CiteSeerx project and codirects the ChemxSeer project at Penn State. He has been associated with Columbia University, the University of Maryland, University of Pennsylvania, Princeton University, and the University of Trento.