Tag Archives: University Relations

Announcement of the 2019 Fellowship Awardees and Highlights from the Google PhD Fellowship Summit



In 2009, Google created the PhD Fellowship Program to recognize and support outstanding graduate students who are doing exceptional research in Computer Science and related fields who seek to influence the future of technology. Now in its eleventh year, these Fellowships have helped support 450 graduate students globally in North America and Europe, Australia, Asia, Africa and India.

Every year, recipients of the Fellowship are invited to a global summit at our Mountain View campus, where they can learn more about Google’s state-of-the-art research, and network with Google’s research community as well as other PhD Fellows from around the world. Below we share some highlights from our most recent summit, and also announce the latest class of Google PhD Fellows.

Summit Highlights
At this year’s summit event, active Google Fellowship recipients were joined by special guests, FLIP (Diversifying Future Leadership in the Professoriate) Alliance Fellows. Research Director Peter Norvig opened the event with a keynote on the fundamental practice of machine learning, followed by a number of talks by prestigious researchers. Among the list of speakers were Research Scientist Peggy Chi, who spoke about crowdsourcing geographically diverse images for use in training data, Senior Google Fellow and SVP of Google Research and Health Jeff Dean, who discussed using deep learning to solve a variety of challenging research problems at Google, and Research Scientist Vinodkumar Prabhakaran, who presented the ethical implications of machine learning, especially around questions of fairness and accountability. See the complete list of insightful talks delivered by all speakers here.
Google and FLIP Alliance Fellows attending the 2019 PhD Fellowship Summit
Google Fellows had the opportunity to present their work in lightning talks to small groups with common research interests. In addition, Google and FLIP Alliance Fellows came together to share their work with Google researchers and each other during a poster session.
Poster session in full swing
2019 Google PhD Fellows
The Google PhD Fellows represent some of the best and brightest young computer science researchers from around the globe, and it is our ongoing goal to support them as they make their mark on the world. Congratulations to all of this year’s awardees! The complete list of recipients is:

Algorithms, Optimizations and Markets
Aidasadat Mousavifar, EPFL Ecole Polytechnique Fédérale de Lausanne
Peilin Zhong, Columbia University
Siddharth Bhandari, Tata Institute of Fundamental Research
Soheil Behnezhad, University of Maryland at College Park
Zhe Feng, Harvard University

Computational Neuroscience
Caroline Haimerl, New York University
Mai Gamal, Nile University

Human Computer Interaction
Catalin Voss, Stanford University
Hua Hua, Australian National University
Zhanna Sarsenbayeva, University of Melbourne

Machine Learning
Abdulsalam Ometere Latifat, African University of Science and Technology Abuja
Adji Bousso Dieng, Columbia University
Blake Woodworth, Toyota Technological Institute at Chicago
Diana Cai, Princeton University
Francesco Locatello, ETH Zurich
Ihsane Gryech, International University Of Rabat, Morocco
Jaemin Yoo, Seoul National University
Maruan Al-Shedivat, Carnegie Mellon University
Ousseynou Mbaye, Alioune Diop University of Bambey
Redani Mbuvha, University of Johannesburg
Shibani Santurkar, Massachusetts Institute of Technology
Takashi Ishida, University of Tokyo

Machine Perception, Speech Technology and Computer Vision
Anshul Mittal, IIT Delhi
Chenxi Liu, Johns Hopkins University
Kayode Kolawole Olaleye, Stellenbosch University
Ruohan Gao, The University of Texas at Austin
Tiancheng Sun, University of California San Diego
Xuanyi Dong, University of Technology Sydney
Yu Liu, Chinese University of Hong Kong
Zhi Tian, University of Adelaide

Mobile Computing
Naoki Kimura, University of Tokyo

Natural Language Processing
Abigail See, Stanford University
Ananya Sai B, IIT Madras
Byeongchang Kim, Seoul National University
Daniel Patrick Fried, UC Berkeley
Hao Peng, University of Washington
Reinald Kim Amplayo, University of Edinburgh
Sungjoon Park, Korea Advanced Institute of Science and Technology

Privacy and Security
Ajith Suresh, Indian Institute of Science
Itsaka Rakotonirina, Inria Nancy
Milad Nasr, University of Massachusetts Amherst
Sarah Ann Scheffler, Boston University

Programming Technology and Software Engineering
Caroline Lemieux, UC Berkeley
Conrad Watt, University of Cambridge
Umang Mathur, University of Illinois at Urbana-Champaign

Quantum Computing
Amy Greene, Massachusetts Institute of Technology
Leonard Wossnig, University College London
Yuan Su, University of Maryland at College Park

Structured Data and Database Management
Amir Gilad, Tel Aviv University
Nofar Carmeli, Technion
Zhuoyue Zhao, University of Utah

Systems and Networking
Chinmay Kulkarni, University of Utah
Nicolai Oswald, University of Edinburgh
Saksham Agarwal, Cornell University

Source: Google AI Blog


A Summary of the Google Flood Forecasting Meets Machine Learning Workshop



Recently, we hosted the Google Flood Forecasting Meets Machine Learning workshop in our Tel Aviv office, which brought hydrology and machine learning experts from Google and the broader research community to discuss existing efforts in this space, build a common vocabulary between these groups, and catalyze promising collaborations. In line with our belief that machine learning has the potential to significantly improve flood forecasting efforts and help the hundreds of millions of people affected by floods every year, this workshop discussed improving flood forecasting by aggregating and sharing large data sets, automating calibration and modeling processes, and applying modern statistical and machine learning tools to the problem.

Panel on challenges and opportunities in flood forecasting, featuring (from left to right): Prof. Paolo Burlando (ETH Zürich), Dr. Tyler Erickson (Google Earth Engine), Dr. Peter Salamon (Joint Research Centre) and Prof. Dawei Han (University of Bristol).
The event was kicked off by Google's Yossi Matias, who discussed recent machine learning work and its potential relevance for flood forecasting, crisis response and AI for Social Good, followed by two introductory sessions aimed at bridging some of the knowledge gap between the two fields - introduction to hydrology for computer scientists by Prof. Peter Molnar of ETH Zürich, and introduction to machine learning for hydrologists by Prof. Yishay Mansour of Tel Aviv University and Google

Included in the 2-day event was a wide range of fascinating talks and posters across the flood forecasting landscape, from both hydrologic and machine learning points of view.

An overview of research areas in flood forecasting addressed in the workshop.
Presentations from the research community included:
Alongside these talks, we presented the various efforts across Google to try and improve flood forecasting and foster collaborations in the field, including:
Additionally, at this workshop we piloted an experimental "ML Consultation" panel, where Googlers Gal Elidan, Sasha Goldshtein and Doron Kukliansky gave advice on how to best use machine learning in several hydrology-related tasks. Finally, we concluded the workshop with a moderated panel on the greatest challenges and opportunities in flood forecasting, with hydrology experts Prof. Paolo Burlando of ETH Zürich, Prof. Dawei Han of the University of Bristol, Dr. Peter Salamon of the Joint Research Centre and Dr. Tyler Erickson of Google Earth Engine.
Flood forecasting is an incredibly important and challenging task that is one part of our larger AI for Social Good efforts. We believe that effective global-scale solutions can be achieved by combining modern techniques with the domain expertise already existing in the field. The workshop was a great first step towards creating much-needed understanding, communication and collaboration between the flood forecasting community and the machine learning community, and we look forward to our continued engagement with the broad research community to tackle this challenge.

Acknowledgements
We would like to thank Avinatan Hassidim, Carla Bromberg, Doron Kukliansky, Efrat Morin, Gal Elidan, Guy Shalev, Jennifer Ye, Nadav Rabani and Sasha Goldshtein for their contributions to making this workshop happen.

Source: Google AI Blog


Google Faculty Research Awards 2018



We just completed another round of the Google Faculty Research Awards, our annual open call for proposals on computer science and related topics, such as quantum computing, machine learning, algorithms and theory, natural language processing and more. Our grants cover tuition for a graduate student and provide both faculty and students the opportunity to work directly with Google researchers and engineers.

This round we received 910 proposals covering 40 countries and over 320 universities. After expert reviews and committee discussions, we decided to fund 158 projects. The subject areas that received the most support this year were human computer interaction, machine learning, machine perception, and systems.

Congratulations to the well-deserving recipients of this round's awards. More information on how to apply for the next round will be available at the end of the summer on our website. You can find award recipients from previous years here.

Source: Google AI Blog


Google’s Workshop on AI/ML Research and Practice in India



Last month, Google Bangalore hosted the Workshop on Artificial Intelligence and Machine Learning, with the goal of fostering collaboration between the academic and industry research communities in India. This forum was designed to exchange current research and industry projects in AI & ML, and included faculty and researchers from Indian Institutes of Technology (IITs) and other leading universities in India, along with industry practitioners from Amazon, Delhivery, Flipkart, LinkedIn, Myntra, Microsoft, Ola and many more. Participants spoke on the ongoing research and work being undertaken in India in deep learning, computer vision, natural language processing, systems and generative models (you can access all the presentations from the workshop here).

Google’s Jeff Dean and Prabhakar Raghavan kicked off the workshop by sharing Google’s uses of deep learning to solve challenging problems and reinventing productivity using AI. Additional keynotes were delivered by Googlers Rajen Sheth and Roberto Bayardo. We also hosted a panel discussion on the challenges and future of AI/ML ecosystem in India, moderated by Google Bangalore’s Pankaj Gupta. Panel participants included Anirban Dasgupta (IIT Gandhinagar), Chiranjib Bhattacharyya of the Indian Institute of Science (IISc), Ashish Tendulkar and Srinivas Raaghav (Google India) and Shourya Roy (American Express Big Data Labs).
Prabhakar Raghavan’s keynote address
Sessions
The workshop agenda included five broad sessions with presentations by attendees in the following areas:
Pankaj Gupta moderating the panel discussion
Summary and Next Steps
As in many countries around the world, we are seeing increased dialog on various aspects of AI and ML in multiple contexts in India. This workshop hosted 80 attendees representing 9 universities and 36 companies contributing 28 excellent talks, with many opportunities for discussing challenges and opportunities for AI/ML in India. Google will continue to foster this exchange of ideas across a diverse set of folks and applications. As part of this, we also announced the upcoming research awards round (applications due June 4) to support up to seven faculty members in India on their AI/ML research, and new work on an accelerator program for Indian entrepreneurs focused primarily on AI/ML technologies. Please keep an eye out for more information about these programs.

Google’s Workshop on AI/ML Research and Practice in India



Last month, Google Bangalore hosted the Workshop on Artificial Intelligence and Machine Learning, with the goal of fostering collaboration between the academic and industry research communities in India. This forum was designed to exchange current research and industry projects in AI & ML, and included faculty and researchers from Indian Institutes of Technology (IITs) and other leading universities in India, along with industry practitioners from Amazon, Delhivery, Flipkart, LinkedIn, Myntra, Microsoft, Ola and many more. Participants spoke on the ongoing research and work being undertaken in India in deep learning, computer vision, natural language processing, systems and generative models (you can access all the presentations from the workshop here).

Google’s Jeff Dean and Prabhakar Raghavan kicked off the workshop by sharing Google’s uses of deep learning to solve challenging problems and reinventing productivity using AI. Additional keynotes were delivered by Googlers Rajen Sheth and Roberto Bayardo. We also hosted a panel discussion on the challenges and future of AI/ML ecosystem in India, moderated by Google Bangalore’s Pankaj Gupta. Panel participants included Anirban Dasgupta (IIT Gandhinagar), Chiranjib Bhattacharyya of the Indian Institute of Science (IISc), Ashish Tendulkar and Srinivas Raaghav (Google India) and Shourya Roy (American Express Big Data Labs).
Prabhakar Raghavan’s keynote address
Sessions
The workshop agenda included five broad sessions with presentations by attendees in the following areas:
Pankaj Gupta moderating the panel discussion
Summary and Next Steps
As in many countries around the world, we are seeing increased dialog on various aspects of AI and ML in multiple contexts in India. This workshop hosted 80 attendees representing 9 universities and 36 companies contributing 28 excellent talks, with many opportunities for discussing challenges and opportunities for AI/ML in India. Google will continue to foster this exchange of ideas across a diverse set of folks and applications. As part of this, we also announced the upcoming research awards round (applications due June 4) to support up to seven faculty members in India on their AI/ML research, and new work on an accelerator program for Indian entrepreneurs focused primarily on AI/ML technologies. Please keep an eye out for more information about these programs.

Source: Google AI Blog


Announcing the 2018 Google PhD Fellows for North America, Europe and the Middle East



Google created the PhD Fellowship program in 2009 to recognize and support outstanding graduate students doing exceptional research in Computer Science and related disciplines. Now in its ninth year, our fellowship program has supported hundreds of future faculty, industry researchers, innovators and entrepreneurs.

Reflecting our continuing commitment to supporting and building relationships with the academic community, we are excited to announce the 39 recipients from North America, Europe and the Middle East. We offer our sincere congratulations to the 2018 Google PhD Fellows.

Algorithms, Optimizations and Markets
Emmanouil Zampetakis, Massachusetts Institute of Technology
Manuela Fischer, ETH Zurich CS
Thodoris Lykouris, Cornell University
Yuan Deng, Duke University

Computational Neuroscience
Ella Batty, Columbia University
Neha Spenta Wadia, University of California, Berkeley
Reuben Feinman, New York University

Human-Computer Interaction
Gierad Laput, Carnegie Mellon University
Mike Schaekermann, University of Waterloo
Minsuk (Brian) Kahng, Georgia Tech

Machine Learning
Aditi Raghunathan, Stanford University
Lin Chen, Yale University
Qian Yu, University of Southern California
Ravid Shwartz-Ziv, The Hebrew University of Jerusalem
Shuang Liu, University of California, San Diego
Stephen Tu, University of California, Berkeley
Xinchen Yan, University of Michigan, Ann Arbor
Zelda Mariet, Massachusetts Institute of Technology

Mobile Computing
Shilin Zhu, University of California, San Diego

Machine Perception, Speech Technology and Computer Vision
Antoine Miech, INRIA
Arsha Nagrani, University of Oxford (ES)
Joseph Redmon, University of Washington
Raymond Yeh, University of Illinois, Urbana-Champaign
Shanmukha Ramakrishna Vedantam, Georgia Tech

Natural Language Processing
Anne Cocos, University of Pennsylvania
Jonathan Herzig, Tel-Aviv University
Rotem Dror, Technion - Israel Institute of Technology
Yang Liu, The University of Edinburgh
Yoon Kim, Harvard University

Privacy and Security
Aayush Jain, University of California, Los Angeles

Programming Technology and Software Engineering
Gowtham Kaki, Purdue University, West Lafayette
Reyhaneh Jabbarvand, University of California, Irvine
Victor Lanvin, Fondation Sciences Mathématiques de Paris

Quantum Computing
Erika Ye, California Institute of Technology

Structured Data and Database Management
Lingjiao Chen, University of Wisconsin

Systems and Networking
Andrea Lattuada, ETH Zurich CS
Lana Josipović, EPFL CS
Michael Schaarschmidt, University of Cambridge - Computer Laboratory
Rachee Singh, University of Massachusetts, Amherst

Source: Google AI Blog


Announcing the 2018 Google PhD Fellows for North America, Europe and the Middle East



Google created the PhD Fellowship program in 2009 to recognize and support outstanding graduate students doing exceptional research in Computer Science and related disciplines. Now in its ninth year, our fellowship program has supported hundreds of future faculty, industry researchers, innovators and entrepreneurs.

Reflecting our continuing commitment to supporting and building relationships with the academic community, we are excited to announce the 39 recipients from North America, Europe and the Middle East. We offer our sincere congratulations to the 2018 Google PhD Fellows.

Algorithms, Optimizations and Markets
Emmanouil Zampetakis, Massachusetts Institute of Technology
Manuela Fischer, ETH Zurich CS
Thodoris Lykouris, Cornell University
Yuan Deng, Duke University

Computational Neuroscience
Ella Batty, Columbia University
Neha Spenta Wadia, University of California, Berkeley
Reuben Feinman, New York University

Human-Computer Interaction
Gierad Laput, Carnegie Mellon University
Mike Schaekermann, University of Waterloo
Minsuk (Brian) Kahng, Georgia Tech

Machine Learning
Aditi Raghunathan, Stanford University
Lin Chen, Yale University
Qian Yu, University of Southern California
Ravid Shwartz-Ziv, The Hebrew University of Jerusalem
Shuang Liu, University of California, San Diego
Stephen Tu, University of California, Berkeley
Xinchen Yan, University of Michigan, Ann Arbor
Zelda Mariet, Massachusetts Institute of Technology

Mobile Computing
Shilin Zhu, University of California, San Diego

Machine Perception, Speech Technology and Computer Vision
Antoine Miech, INRIA
Arsha Nagrani, University of Oxford (ES)
Joseph Redmon, University of Washington
Raymond Yeh, University of Illinois, Urbana-Champaign
Shanmukha Ramakrishna Vedantam, Georgia Tech

Natural Language Processing
Anne Cocos, University of Pennsylvania
Jonathan Herzig, Tel-Aviv University
Rotem Dror, Technion - Israel Institute of Technology
Yang Liu, The University of Edinburgh
Yoon Kim, Harvard University

Privacy and Security
Aayush Jain, University of California, Los Angeles

Programming Technology and Software Engineering
Gowtham Kaki, Purdue University, West Lafayette
Reyhaneh Jabbarvand, University of California, Irvine
Victor Lanvin, Fondation Sciences Mathématiques de Paris

Quantum Computing
Erika Ye, California Institute of Technology

Structured Data and Database Management
Lingjiao Chen, University of Wisconsin

Systems and Networking
Andrea Lattuada, ETH Zurich CS
Lana Josipović, EPFL CS
Michael Schaarschmidt, University of Cambridge - Computer Laboratory
Rachee Singh, University of Massachusetts, Amherst

Investing in France’s AI Ecosystem



Recently, we announced the launch of a new AI research team in our Paris office. And today DeepMind has also announced a new AI research presence in Paris. We are excited about expanding Google’s research presence in Europe, which bolsters the efforts of the existing groups in our Zürich and London offices. As strong supporters of academic research, we are also excited to foster collaborations with France’s vibrant academic ecosystem.

Our research teams in Paris will focus on fundamental AI research, as well as important applications of these ideas to areas such as Health, Science or Arts. They will publish and open-source their results to advance the state-of-the-art in core areas such as Deep Learning and Reinforcement Learning.

Our approach to research is based on building a strong connection with the academic community; contributing to training the next generation of scientists and establishing a bridge between academic and industrial research. We believe that both objectives are key to fostering a healthy research ecosystem that will flourish in the long term. These ideas are very much aligned with some of the recommendations that Fields Medalist and member of French Parliament Cédric Villani is putting forward in his report on AI to the French government.

As we expand our teams in France, we have several initiatives that illustrate our commitment to these goals:
  • We are sponsoring “Artificial Intelligence and Visual Computing” Chair at École Polytechnique (one of the leading higher education institutions in France) which will support their education initiatives in AI
  • We just established a partnership with INRIA for conducting collaborative research projects
  • We are funding academic research with unrestricted grants mostly dedicated to the support of PhD and postdoc positions through our Faculty Research Awards and PhD Fellowship programs, as well as our Focused Research Awards. As one example, we have recently funded a project on large scale optimization of neural networks led by Francis Bach (INRIA and ENS) and Alexandre d’Aspremont (CNRS and ENS)
  • We are working on offering CIFRE PhD positions (joint PhD positions between Google and an academic lab) as well as internships for PhD students
Additionally, we are pleased to announce that one of the world’s leading experts in computer vision, Cordelia Schmid, will begin a dual appointment at INRIA and Google Paris. These kind of appointments, together with our Visiting Faculty program, are a great way to share ideas and research challenges, and utilize Google's world-class computing infrastructure to explore new projects at industrial scale.

France has a long tradition of research and educational excellence, and has a very dynamic and active machine learning community. This makes it a great place to pursue our goal of building AI-enabled technologies that can benefit everyone, through fundamental advances in machine learning and related fields.

Source: Google AI Blog


Investing in France’s AI Ecosystem



Recently, we announced the launch of a new AI research team in our Paris office. And today DeepMind has also announced a new AI research presence in Paris. We are excited about expanding Google’s research presence in Europe, which bolsters the efforts of the existing groups in our Zürich and London offices. As strong supporters of academic research, we are also excited to foster collaborations with France’s vibrant academic ecosystem.

Our research teams in Paris will focus on fundamental AI research, as well as important applications of these ideas to areas such as Health, Science or Arts. They will publish and open-source their results to advance the state-of-the-art in core areas such as Deep Learning and Reinforcement Learning.

Our approach to research is based on building a strong connection with the academic community; contributing to training the next generation of scientists and establishing a bridge between academic and industrial research. We believe that both objectives are key to fostering a healthy research ecosystem that will flourish in the long term. These ideas are very much aligned with some of the recommendations that Fields Medalist and member of French Parliament Cédric Villani is putting forward in his report on AI to the French government.

As we expand our teams in France, we have several initiatives that illustrate our commitment to these goals:
  • We are sponsoring “Artificial Intelligence and Visual Computing” Chair at École Polytechnique (one of the leading higher education institutions in France) which will support their education initiatives in AI
  • We just established a partnership with INRIA for conducting collaborative research projects
  • We are funding academic research with unrestricted grants mostly dedicated to the support of PhD and postdoc positions through our Faculty Research Awards and PhD Fellowship programs, as well as our Focused Research Awards. As one example, we have recently funded a project on large scale optimization of neural networks led by Francis Bach (INRIA and ENS) and Alexandre d’Aspremont (CNRS and ENS)
  • We are working on offering CIFRE PhD positions (joint PhD positions between Google and an academic lab) as well as internships for PhD students
Additionally, we are pleased to announce that one of the world’s leading experts in computer vision, Cordelia Schmid, will begin a dual appointment at INRIA and Google Paris. These kind of appointments, together with our Visiting Faculty program, are a great way to share ideas and research challenges, and utilize Google's world-class computing infrastructure to explore new projects at industrial scale.

France has a long tradition of research and educational excellence, and has a very dynamic and active machine learning community. This makes it a great place to pursue our goal of building AI-enabled technologies that can benefit everyone, through fundamental advances in machine learning and related fields.

Google Faculty Research Awards 2017



We’ve just completed another round of the Google Faculty Research Awards, our annual open call for proposals on computer science and related topics such as machine learning, machine perception, natural language processing, and quantum computing. Our grants cover tuition for a graduate student and provide both faculty and students the opportunity to work directly with Google researchers and engineers.

This round we received 1033 proposals covering 46 countries and over 360 universities. After expert reviews and committee discussions, we decided to fund 152 projects. The subject areas that received the most support this year were human computer interaction, machine learning, machine perception, and systems. Here are a few observations from this round:
  • There was a 17% increase in the total number of proposals received
  • There was a 87% increase in the number of proposals from Asia Pacific universities
  • Proposals focused on Computational Neuroscience increased 53%
  • Proposals focused on Quantum Computing more than doubled this round
Congratulations to the well-deserving recipients of this round’s awards. If you are interested in applying for the next round (September 2018 deadline), please visit our website for more information. You can find award recipients from previous years here.

Source: Google AI Blog