Dr. Avinatan Hassidim received his Ph.D in quantum computing from the Hebrew University in 2008. He spent two years at MIT RLE as a Keck fellow, and then joined Google research, and the faculty at Bar Ilan University. Avinatan received the SIGMETRICS 2011 Best Paper award, the INFOCOM 2012 Runner up for Best Paper award, and the INFOCOM 2013 Runner up for Best Paper award.
Avinatan is the designer of the Israeli medical internship lottery, and the Israeli psychology match.
Blaise Agüera y Arcas
Blaise leads Google's on-device Machine Intelligence programs—including both basic research and new products. His group works extensively with deep neural nets for machine perception, distributed learning, machine creativity, and agents, as well as collaborating with academic institutions on computational neuroscience and connectomics research. Until 2014 he was a Distinguished Engineer at Microsoft, where he worked in a variety of roles, from inventor to strategist, and led teams with strengths in interaction design, prototyping, machine vision, augmented reality, wearable computing and graphics. Blaise has given TED talks on Seadragon and Photosynth (2007, 2012), Bing Maps (2010), and machine creativity (2016). In 2008, he was awarded MIT’s TR35 prize.
Deborah Cohen received the B.Sc. degree in electrical engineering (summa cum laude) in 2010 and the Ph.D. degree in electrical engineering (signal processing) in 2016 from the Technion - Israel Institute of Technology, Haifa, in 2010. Since 2010, she has been a Project Supervisor with the Signal and Image Processing Lab, the High Speed Digital Systems Lab, the Communications Lab and the Signal Acquisition, Modeling and Processing Lab (SAMPL), at the Electrical Engineering Department, Technion. In 2011, Ms. Cohen was awarded the Meyer Foundation Excellence prize. She received the Sandor Szego Award and the Vivian Konigsberg Award for Excellence in Teaching from 2012 to 2016, the David and Tova Freud and Ruth Freud-Brendel Memorial Scholarship in 2014 and the Muriel and David Jacknow Award for Excellence in Teaching in 2015. Since 2014, Ms. Cohen is an Azrieli Fellow. She is currently a research scientist in the Clair team in Google Israel. Her research interests include theoretical aspects of signal processing, compressed sensing, reinforcement learning and machine learning for dialogues.
Gal is a research scientist at Google and leads Clair, the new Israeli ML research team. He received his Ph.D. from the School of Computer Science and Engineering at the Hebrew University, and is now also a professor at the Department of Statistics at the Hebrew University, where his research focuses on representation and structure in probabilistic graphical models.
Dr. Idan Szpektor is a sr. research scientist at Google. Before that, he was a sr. research scientist at Yahoo Research for seven years. Idan’s research is focused on Natural Language Processing and its applications in Web technologies. Recently, he studies dialogue modeling as well as NLP for healthcare. Idan serves on the editorial board of the Natural Language Engineering journal and he co-organized the WebQA'15 and WebQA'16 workshops. Idan co-authored over 40 publications and he is a recipient of the best paper honorable mention at ECIR'16 and of best paper runner-up awards at ACL'13 and CoNLL'14. He earned his PhD in computer science from Bar-Ilan University, Israel, in 2009.
Jonathon Shlens received his Ph.D in computational neuroscience from UC San Diego in 2007 where his research focused on applying machine learning towards understanding visual processing in real biological systems. He was previously a research fellow at the Howard Hughes Medical Institute, a research engineer at Pixar Animation Studios and a Miller Fellow at UC Berkeley. He has been at Google Research since 2010 and is currently a research scientist focused on building scalable vision systems. During his time at Google, he has been a core contributor to deep learning systems including the recently open-sourced TensorFlow. His research interests have spanned the development of state-of-the-art image recognition systems and training algorithms for deep networks.
Mariano, Senior Software Engineer at Google, was for many years Senior Member of the Technical Staff at Texas Instruments, serving in TI’s Broadband group as Software Manager, Chief Software Architect, and Manager of Methodologies. Mariano did his Phd in ML at Tel Aviv university, and received the Dan-David Prize scholar (2014). Mariano’s Machine Learning research focuses on robustness, mainly in the theory and practice of strategies for autonomous software agents.
Dr. Mike Schuster graduated in Electric Engineering from the Gerhard-Mercator University in Duisburg, Germany in 1993. After receiving a scholarship he spent a year in Japan to study Japanese in Kyoto and Fiber Optics in the Kikuchi laboratory at Tokyo University. His professional career in machine learning and speech brought him to Advanced Telecommunications Research Laboratories in Kyoto, Nuance in the US and NTT in Japan where he worked on general machine learning and speech recognition research and development after getting his PhD at the Nara Institute of Science and Technology. Dr. Schuster joined the Google speech group in the beginning of 2006, seeing speech products being developed from scratch to toy demos to serving millions of users in many languages over the next eight years, and he was the main developer of the original Japanese and Korean speech recognition models. He is now part of the Google Brain group which focuses on building large-scale neural network and machine learning infrastructure for Google and has been working on infrastructure with the TensorFlow toolkit as well as on research, mostly in the field of speech and translation with various types of recurrent neural networks. In 2016 he led the development of the new Google Neural Machine Translation system, which reduced translation errors by more than 60% compared to the previous system.
Michael joined Google in 2006, as one of the first engineers in the Israel R&D office. He has since then been leading and managing the Autocomplete engineering team. Autocomplete provides users with query predictions as they type a query in a search box. Michael’s team is responsible for launching, maintaining, and developing Autocomplete on search boxes across Google’s main products, including Web Search, Chrome, Youtube, Image Search, Gmail, and Maps. Prior to joining Google, Michael worked 9 years at IBM in the Search Technology department at the IBM Haifa R&D Labs. He holds a B.Sc. in Computer Science from the Technion.
Mor Schlesinger started her high-tech career at the age of 17, and spent more than 25 years in a variety of roles as a software engineer, entrepreneur and a senior executive in the mobile, Internet, engineering and defense industries.
Mor is an Engineering Manager at Google, working on Crisis Response in Search, and focusing on getting people the right information at the times they need it most. In her most recent role she served as Vice President of Engineering at Quixey, a mobile technology company focused on providing users with easy access and engagement with the content and functionalities within apps. In this role, Mor established the Israeli office and led the engineering team at Quixey Israel. Prior to Quixey, Mor spent time at SharedBook (as its VP R&D and co-founder), Vigil, Technomatix/Siemens, IBM and she also served as an officer in the IDF intelligence corps.
Mor holds a BSc cum laude in mathematics and computer science from Tel Aviv University and MSc cum laude in computer science.
Throughout the years Mor has been actively volunteering with women empowerment organizations, and is working closely with SheCodes as a mentor, speaker and in its advisory board.
Roni Rabin joined Google in 2011 as an engineer on the Google Trends team, over the years she grew her responsibilities and is now the engineering manager of the team. In this role, Roni leads a team of ~20 engineers in building the next generation of Trends products for journalists, researchers and consumers. Roni earned her BSc. in Software Engineering at the Technion - Israel Institute of Technology.
Yehuda Koren is a staff research scientist at Google. Prior to this, he was a senior research scientist at Yahoo! Research and a principal staff member of AT&T Labs-Research. He received the PhD degree in computer science from The Weizmann Institute. His main research interests are recommender systems, data mining, machine learning, IR, and information visualization. He led the team that won the two progress awards in the Netflix Prize competition, and was part of the team which won the Netflix Grand Prize. Dr. Koren has more than 50 research publications and several patents to his credit. He was awarded the best paper awards at INFOVIS 2005, KDD 2009, and RecSys 2011.He served as program co-chair of KDD'13 and RecSys'14, as a senior program committee member at conferences like KDD, ICDM, RecSys, WSDM, and CIKM, and on the editorial board of IEEE TKDE and ACM TIST.
Yoram Singer is a research scientist at Google. He heads a small research group, which focuses on foundations of machine learning. Before joining Google, he was a professor of Computer Science at the Hebrew University of Jerusalem. Starting September 2017, he will be again a professor of Computer Science at Princeton University.
Yossi Matias is Vice President, Engineering, at Google and the Managing Director of Google's R&D Center in Israel which he established. He leads efforts in Search, Research and Machine Intelligence, and Crisis Response, and is the founding executive lead of Google's Campus Tel Aviv. In addition to his experience as entrepreneur and executive, Yossi has been on the Computer Science faculty at Tel Aviv University, and previously a Research Scientist at Bell Labs and visiting professor at Stanford. He published extensively and pioneered some of the early technologies for the effective analysis of big data, internet privacy, and contextual search. Yossi is a recipient of the Godel Prize and is an ACM Fellow for contributions to analysis of big data. (bio)