Yossi Matias is Vice President, Engineering, at Google. He is leading strategic efforts in Search (Google Autocomplete, Search Live Results, Google Trends, Search Console), Conversational AI (Google Duplex, Call Screen, Live Caption, Read Aloud), and other Research initiatives (from foundations to applications in Health). He is the global lead of Crisis Response (SOS Alerts, Public Alerts, Flood Forecasting), and is a founding co-lead of Google’s AI for Social Good initiative.

Yossi is the founding Managing Director of Google's Center in Israel, which he established and grew to over 1500 on staff. He is on the board of IATI and co-chair of its multinational company forum. He is the founding exec lead of Google for Startup Campus Tel Aviv, and of Launchpad and other global entrepreneurship programs. 

Prof. Matias is on the CS faculty of Tel Aviv University, and previously a Research Scientist at Bell Labs and visiting professor at Stanford. He published extensively, has over 60 patents on his name, and pioneered some of the early technologies for the effective analysis of big data, internet privacy, and contextual search. 

Yossi is an ACM Fellow and a recipient of the Godel Prize and of the Kanellakis Theory and Practice Award for seminal work on the foundations of streaming algorithms and their application to large-scale data analytics.

Jonathan Berant is an associate professor at the School of Computer Science at Tel Aviv University and a research scientist at The Allen Institute for AI. Jonathan earned a Ph.D. in Computer Science at Tel-Aviv University, under the supervision of Prof. Ido Dagan. Jonathan was a post-doctoral fellow at Stanford University, working with Prof. Christopher Manning and Prof. Percy Liang, and subsequently a post-doctoral fellow at Google Research, Mountain View. Jonathan Received several awards and fellowships including The Rothschild fellowship, The ACL 2011 best student paper award, EMNLP 2014 best paper award, and NAACL 2019 best resource paper award, as well as several honorable mentions. Jonathan is currently an ERC grantee.

Gal Chechik is a Professor at the Gonda Brain research institute and a director of AI at NVIDIA. His research spans learning in brains and machines, including large-scale learning algorithms for machine perception, and analysis of representation and changes of mammalian brains.

Gal earned his PhD in 2004 from the Hebrew University developing machine learning methods to study neural coding. He then worked at Stanford CS department with D. Koller, studying computational principles regulating molecular pathways. In 2007 he joined Google research as a senior research scientist, developing large scale machine learning algorithm for machine perception. Since 2009, he heads the learning systems lab at the Gonda center of Bar Ilan university, and was appointed an associate professor in 2013. Gal is the author of ~80 refereed publications, including publications in Nature Biotechnology, Cell and PNAS. He was awarded a fullbright fellowship, a complexity scholarship and an Alon fellowship. In 2018 he joined NVIDIA as a director of AI, leading nvidia's research in Israel.

Born and raised in Tel Aviv, Ariel Porat served as an officer in the “8200” IDF Intelligence Corps unit for 5 years. He subsequently enrolled in law studies at Tel Aviv University, where he earned his LLB and direct JSD before performing post-doctoral studies at Yale Law School. His main research areas are torts, contracts, remedies, and law and economics.

He joined the Tel Aviv University faculty in 1990. From 2002 to 2006, he served as Dean of the Buchmann Faculty of Law, where he introduced a number of joint LLM programs and student exchange programs with leading schools abroad, and from 2013 to 2014 he chaired the University Strategic Steering Committee tasked with the academic restructuring of the University.

Driven by a deep sense of social responsibility, Porat conceived and launched a pioneering admittance program at TAU for students from Israel’s geographic and social periphery, and was additionally involved in other initiatives intended to widen the circle of educational opportunity for underrepresented groups in Israel.

Porat is Alain Poher Professor of Law at TAU and Associate Member and Fischel-Neil Distinguished Visiting Professor of Law at the University of Chicago. He was also a Visiting Professor at the University of California at Berkeley, Columbia University, New York University, Stanford University, University of Toronto and the University of Virginia. He is a member of the American Law Institute, a former board member of the American Law and Economics Association and a former president of the Israeli Law and Economics Association. From 1997 to 2002, he was the Director of TAU’s Cegla Center for Interdisciplinary Research of the Law. He is the founder of the journal Theoretical Inquiries in Law and was its editor-in-chief in the years 1999-2003.

Porat is the author of four books and more than 90 articles published by the world’s leading academic presses and scholarly journals.

Shie Mannor has been with the Faculty of Electrical Engineering at the Technion since 2008 where he is a professor, the co-director of the Technion Machine Learning and Intelligent Systems Center, and the Edwards Chair in Engineering. Shie is also a distinguished scientist at Nvidia Research. Shie has published over 250 papers in leading venues and holds 10 patents. His papers were cited over 17,000 times and his h-index is 64. Shie’s research interests include machine learning and data science with an emphasis on reinforcement learning, planning and control, and analysis and control of large-scale systems. Shie has been active in the high-tech industry in Israel, Canada and the US where he has consulted to dozens of companies over the years and has co-founded four companies.
 

Nadav Cohen is an Asst. Professor of Computer Science at Tel Aviv University, and Chief Scientist at Imubit.  His academic research revolves around the theoretical and algorithmic foundations of deep learning, while at Imubit he leads the development of deep learning systems controlling industrial manufacturing lines.  Nadav earned a BSc in electrical engineering and a BSc in mathematics (both summa cum laude) at the Technion Excellence Program for Distinguished Undergraduates.  He obtained his PhD (direct track, summa cum laude) at the Hebrew University, and was subsequently a postdoctoral scholar at the Institute for Advanced Study in Princeton.  For his contributions to deep learning, Nadav won a number of awards, including the Google Doctoral Fellowship in Machine Learning, the Final Prize for Machine Learning Research, the Rothschild Postdoctoral Fellowship, the Zuckerman Postdoctoral Fellowship, and TheMarker's 40 under 40 list.

Karine Nahon is the elected president of the Israel Internet Association (ISOC-IL), an Associate Professor of Information Science in the Lauder School of Government and Ofer School of Communications at the Interdisciplinary Center at Herzliya (IDC), Israel, and an Affiliated Associate Professor in the Information School at University of Washington (UW). She is a member of the Social Media Lab (SoMe Lab), affiliated faculty at the Center for Communication and Civic Engagement at University of Washington. She is the former director of the Virality of Information (retroV) research group and former director of the Center for Information & Society at University of Washington.

Using interdisciplinary lenses, her research focuses on politics of information, and information politics. More specifically, she studies power dynamics and network gatekeeping in social media, and the role of virality and information flows in elections and in politics in general. Professor Nahon is the author of the book Going Viral 2013 (co-authored with Jeff Hemsley). The book received the ASIS&T Best Information Science Book Award, The American Library Association Outstanding Academic Titles. She has published over 80 research papers in her area in top-tier journals like JASIS&T, ARIST, JCMC, IJoC, ICS and TIS. Since 2013 she serves as the co-chair of the Digital and Social Media track at HICSS.

Hayit Greenspan is a Professor of Biomedical Engineering in the Faculty of Engineering, Tel-Aviv University. Dr. Greenspan received the B.S. and M.S. degrees in Electrical Engineering (EE) from the Technion, and the Ph.D. degree in EE from CALTECH – California Institute of Technology. She was a Postdoc with the CS Division at U.C. Berkeley following which she joined Tel-Aviv University.  From 2008 until 2011, she was a visiting Professor at Stanford University, Department of Radiology, Faculty of Medicine. She was also a visiting researcher at IBM Research in the Multi-modal Mining for Healthcare group, in Almaden CA.
 

Dr. Greenspan has over 150 publications in leading international journals and conferences and has received several awards and patents. She is member of several journal and conference program committees, including SPIE medical imaging, IEEE_ISBI and MICCAI.  She served as an Associate Editor for the IEEE Trans on Medical Imaging (TMI) journal.  In 2016 she was the Lead Co-editor for a Special issue on Deep Learning in Medical Imaging in IEEE TMI. In 2017 she Co-edited an Elsevier Academic Press book on Deep learning for Medical Image Analysis. Recently she was titled as one of the Top-30 Women AI leaders in Drug Discovery and Advanced Healthcare, by Deep Knowledge Analytics (www.ai-pharma.dka.global/top-30-women).

Professor Irad Ben-Gal is the head of the Laboratory of AI Business & Data Analytics (LAMBDA) at the Engineering Faculty in Tel Aviv University. He held a visiting professor position at Stanford University, teaching “analytics in action” and co-heading the TAU/Stanford “Digital Living 2030” research initiative that focuses on future challenges of modern digital life. Irad is a world-renowned expert in practical machine learning, statistical process control and predictive analytics with more than 20 years of experience in the field, including R&D collaborations with companies such as Oracle, Intel, GM, AT&T, Applied Materials and Nokia. He wrote four books, published more than 100 scientific papers and patents, supervised dozens of graduate students and received numerous awards for his work. Irad is the co-founder and chairman of CB4 (“See Before”), a startup backed by Sequoia Capital that provides predictive analytics solutions to retail organizations. He is an advisory board member in several startup companies that focus on AI applications.

Tamir Hazan received his PhD from the Hebrew University of Jerusalem and he is currently an assistant professor at the Technion. Tamir Hazan’s research describes efficient methods for reasoning about structured models and recently on structured attention models in deep learning. His work on random perturbations enables to propagate gradients through discrete structured predictions in deep nets and a book on these contributions was published by MIT Press on 2016, and was acknowledged by a best paper shortlist at ICML 2012 and in the machine learning best papers track at AAAI 2012. Tamir Hazan’s research also includes the primal-dual norm-product belief propagation algorithm which received a best paper award at UAI 2008.

Gal is a senior data scientist at PayPal, working mostly on NLP applications and NLP variable generation. She currently heads up construction of an internal NLP infrastructure to feed a wide variety of models in diverse domains like fraud detection, marketing, and Credit risk. Gal holds a BSc in Electrical Engineering and Physics as well as an MSc in Electrical engineering, all from Tel Aviv University. Before PayPal, Gal worked as a guidance and control algorithms engineer for aerospace systems and later as a data scientist on cyber applications.

Mariarosaria Taddeo is Associate Professor and Senior Research Fellow at the Oxford Internet Institute, University of Oxford, where she is the Deputy Director of the Digital Ethics Lab, and is Faculty Fellow and Defence Science and Technology Fellow at the Alan Turing Institute. Her recent work focuses mainly on the ethical analysis of Artificial Intelligence, cyber security , cyber conflicts, and ethics of digital innovation. Her area of expertise is Philosophy and Ethics of Information, although she has worked on issues concerning Epistemology, Logic, and Philosophy of AI. She has received multiple award for her work, among which the 2010 Simon Award for Outstanding Research in Computing and Philosophy; the 2016 World Technology Award for Ethics. In 2018, InspiringFifty named her among the most inspiring 50 Italian women working in technology. In the same year, ORBIT listed her among the top 100 women working on Ethics of AI in the world. She has been named one of the twelve 2020 "Outstanding Rising Talents" by the Womens' Forum for Economy and Society. Since 2016, Taddeo serves as editor-in-chief of Minds & Machines (SpringerNature) and of Philosophical Studies Series (SpringerNature). She is also a member of the Exploratory Team on Operational Ethics, established under the auspices of the Human Factors and Medicine (HFM) panel of the NATO Science and Technology Organization. Her research has been published in major journals like Nature, Nature Machine Intelligence, Science, and Science Robotics.

Yedid Hoshen is an Assistant Professor at the School of Computer Science and Engineering, the Hebrew University of Jerusalem. His current research interests include Deep Generative Models, Representation Disentanglement and Anomaly Detection. Recently, he was a Research Scientist at Facebook AI Research. He completed his PhD at the Hebrew University of Jerusalem, supervised by Prof. Shmuel Peleg. Previously he studied Physics at the University of Oxford, traded options (volatility arbitrage) for a prop desk at KBC-FP, designed mission control algorithms for the Israeli Space Program and worked at Google ([x] and Research).

I am a senior lecturer at Tel Aviv University’s school of computer science and a research scientist at Facebook AI Research. I completed my BSc and MSc at Technion and my PhD at Bar-Ilan University, and did postdoctoral research at the University of Washington. Research: My research is in the intersection of natural language processing (NLP) and machine learning. I have worked on a variety of topics including semantics, self-supervised learning, machine translation, language modeling, dataset annotation, and explainability. I am particularly interested in creating NLP models that can generalize well.

https://www.cs.tau.ac.il/~levyomer/