Google Research Blog
The latest news from Research at Google
Announcing Google’s 2015 Global PhD Fellows
Friday, August 28, 2015
Posted by Michael Rennaker, Google University Relations
In 2009, Google created the
PhD Fellowship program
to recognize and support outstanding graduate students doing exceptional research in Computer Science and related disciplines. Now in its seventh year, our fellowship programs have collectively supported over 200 graduate students in
Australia
,
China and East Asia
,
India
,
North America
,
Europe and the Middle East
who seek to shape and influence the future of technology.
Reflecting our continuing commitment to building mutually beneficial relationships with the academic community, we are excited to announce the 44 students from around the globe who are recipients of the award. We offer our sincere congratulations to Google’s 2015 Class of PhD Fellows!
Australia
Bahar Salehi
, Natural Language Processing (University of Melbourne)
Siqi Liu
, Computational Neuroscience (University of Sydney)
Qian Ge
, Systems (University of New South Wales)
China and East Asia
Bo Xin
, Artificial Intelligence (Peking University)
Xingyu Zeng
, Computer Vision (The Chinese University of Hong Kong)
Suining He
, Mobile Computing (The Hong Kong University of Science and Technology)
Zhenzhe Zheng
, Mobile Networking (Shanghai Jiao Tong University)
Jinpeng Wang
, Natural Language Processing (Peking University)
Zijia Lin
, Search and Information Retrieval (Tsinghua University)
Shinae Woo
, Networking and Distributed Systems (Korea Advanced Institute of Science and Technology)
Jungdam Won
, Robotics (Seoul National University)
India
Palash Dey
, Algorithms (Indian Institute of Science)
Avisek Lahiri
, Machine Perception (Indian Institute of Technology Kharagpur)
Malavika Samak
, Programming Languages and Software Engineering (Indian Institute of Science)
Europe and the Middle East
Heike Adel
, Natural Language Processing (University of Munich)
Thang Bui
, Speech Technology (University of Cambridge)
Victoria Caparrós Cabezas
, Distributed Systems (ETH Zurich)
Nadav Cohen
, Machine Learning (The Hebrew University of Jerusalem)
Josip Djolonga
, Probabilistic Inference (ETH Zurich)
Jakob Julian Engel
, Computer Vision (Technische Universität München)
Nikola Gvozdiev
, Computer Networking (University College London)
Felix Hill
, Language Understanding (University of Cambridge)
Durk Kingma
, Deep Learning (University of Amsterdam)
Massimo Nicosia
, Statistical Natural Language Processing (University of Trento)
George Prekas
, Operating Systems (École Polytechnique Fédérale de Lausanne)
Roman Prutkin
, Graph Algorithms (Karlsruhe Institute of Technology)
Siva Reddy
, Multilingual Semantic Parsing (The University of Edinburgh)
Immanuel Trummer
, Structured Data Analysis (École Polytechnique Fédérale de Lausanne)
Margarita Vald
, Security (Tel Aviv University)
North America
Waleed Ammar
, Natural Language Processing (Carnegie Mellon University)
Justin Meza
, Systems Reliability (Carnegie Mellon University)
Nick Arnosti
, Market Algorithms (Stanford University)
Osbert Bastani
, Programming Languages (Stanford University)
Saurabh Gupta
, Computer Vision (University of California, Berkeley)
Masoud Moshref Javadi
, Computer Networking (University of Southern California)
Muhammad Naveed
, Security (University of Illinois at Urbana-Champaign)
Aaron Parks
, Mobile Networking (University of Washington)
Kyle Rector
, Human Computer Interaction (University of Washington)
Riley Spahn
, Privacy (Columbia University)
Yun Teng
, Computer Graphics (University of California, Santa Barbara)
Carl Vondrick
, Machine Perception, (Massachusetts Institute of Technology)
Xiaolan Wang
, Structured Data (University of Massachusetts Amherst)
Tan Zhang
, Mobile Systems (University of Wisconsin-Madison)
Wojciech Zaremba
, Machine Learning (New York University)
Google Faculty Research Awards: Summer 2015
Friday, August 21, 2015
posted by Maggie Johnson, Director of Education and University Relations
We have just completed another round of the
Google Faculty Research Awards
, our annual open call for research proposals on Computer Science and related topics, including systems, machine learning, software engineering, security and mobile. 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 805 proposals, about the same as
last round
, covering 48 countries on 6 continents. After expert reviews and committee discussions, we decided to fund 113 projects, with 27% of the funding awarded to universities outside the U.S. The subject areas that received the highest level of support were systems, machine perception, software engineering, and machine learning.
The Faculty Research Awards program plays a critical role in building and maintaining strong collaborations with top research faculty globally. These relationships allow us to keep a pulse on what’s happening in academia in strategic areas, and they help to extend our research capabilities and programs. Faculty also report, through our annual survey, that they and their students benefit from a direct connection to Google as a source of ideas and perspective.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is October 15), please visit
our website
for more information.
Announcing the 2015 Google European Doctoral Fellows
Friday, June 05, 2015
Posted by David Harper, University Relations and Beate List, Research Programs
In 2009, Google created the
PhD Fellowship program
to recognize and support outstanding graduate students doing exceptional work in Computer Science and related disciplines. The following year, we launched the program in Europe as the
Google European Doctoral Fellowship program
. Alumni of the European program occupy a variety of positions including faculty positions (
Ofer Meshi
,
Cynthia Liem
), academic research positions (
Roland Angst
,
Carola Doerr
née Winzen) and positions in industry (
Yair Adato
,
Peter Hosek
,
Neil Houlsby
).
Reflecting our continuing commitment to building strong relations with the European academic community, we are delighted to announce the 2015 Google European Doctoral Fellows. The following fifteen fellowship recipients were selected from an outstanding set of PhD students nominated by our partner universities:
Heike Adel
, Fellowship in Natural Language Processing (University of Munich)
Thang Bui,
Fellowship in Speech Technology (University of Cambridge)
Victoria Caparrós Cabezas
, Fellowship in Distributed Systems (ETH Zurich)
Nadav Cohen
, Fellowship in Machine Learning (The Hebrew University of Jerusalem)
Josip Djolonga
, Fellowship in Probabilistic Inference (ETH Zurich)
Jakob Julian Engel
, Fellowship in Computer Vision (Technische Universität München)
Nikola Gvozdiev
, Fellowship in Computer Networking (University College London)
Felix Hill
, Fellowship in Language Understanding (University of Cambridge)
Durk Kingma
, Fellowship in Deep Learning (University of Amsterdam)
Massimo Nicosia
, Fellowship in Statistical Natural Language Processing (University of Trento)
George Prekas
, Fellowship in Operating Systems (École Polytechnique Fédérale de Lausanne)
Roman Prutkin
, Fellowship in Graph Algorithms (Karlsruhe Institute of Technology)
Siva Reddy
, Fellowship in Multilingual Semantic Parsing (The University of Edinburgh)
Immanuel Trummer
, Fellowship in Structured Data Analysis (École Polytechnique Fédérale de Lausanne)
Margarita Vald
, Fellowship in Security (Tel Aviv University)
This group of students represent the next generation of researchers who will endeavor to solve some of the most interesting challenges in Computer Science. We offer our congratulations, and look forward to their future contributions to the research community with high expectation.
Google Computer Science Capacity Awards
Monday, March 16, 2015
By Maggie Johnson, Director of Education and University Relations and Chris Busselle, Google.org
One of Google's goals is to surface successful strategies that support the expansion of high-quality Computer Science (CS) programs at the undergraduate level. Innovations in teaching and technologies, while additionally ensuring better engagement of women and underrepresented minority students, is necessary in creating inclusive, sustainable, and scalable educational programs.
To address issues arising from the
dramatic increase in undergraduate CS enrollments
, we recently launched the Computer Science Capacity Awards program. For this three-year program, select educational institutions were invited to contribute proposals for innovative, inclusive, and sustainable approaches to address current scaling issues in university CS educational programs.
Today, after an extensive proposal review process, we are pleased to announce the recipients of the Capacity Awards program:
Carnegie Mellon University - Professor Jacobo Carrasquel
Alternate Instructional Model for Introductory Computer Science Classes
CMU will develop a new instructional model consisting of two optional mini lectures per week given by the instructor, and problem-solving sessions with flexible group meetings that are coordinated by undergraduate and graduate teaching assistants.
Duke University - Professor Jeffrey Forbes
North Carolina State University - Professor Kristy Boyer
University of North Carolina - Professor Ketan Mayer-Patel
RESEARCH TRIANGLE PEER TEACHING FELLOWS: Scalable Evidence-Based Peer Teaching for Improving CS Capacity and Diversity
The project hopes to increase CS retention and diversity by developing a highly scalable, effective, evidence-based peer training program across three universities in the North Carolina Research Triangle.
Mount Holyoke College - Professor Heather Pon-Barry
MaGE (Megas and Gigas Educate): Growing Computer Science Capacity at Mount Holyoke College
Mount Holyoke’s
MaGE program
includes a plan to grow enrollment in introductory CS courses, particularly for women and other underrepresented groups. The program also includes a plan of action for CS students to educate, mentor, and support others in inclusive ways.
George Mason University - Professor Jeff Offutt
SPARC: Self-PAced Learning increases Retention and Capacity
George Mason University wants to replace the traditional course model for CS-1 and CS-2 with an innovative teaching model of self- paced introductory programming courses. Students will periodically demonstrate competency with practical skills demonstrations similar to those used in martial arts.
Rutgers University - Professor Andrew Tjang
Increasing the Scalability and Diversity in the Face of Large Growth in Computer Science Enrollment
Rutger’s program addresses scalability issues with technology tools, as well as collaborative spaces. It also emphasizes outreach to Rutgers’ women’s college and includes original research on success in CS programs to create new courses that cater to the changing environment.
University of California, Berkeley - Professor John DeNero
Scaling Computer Science through Targeted Engagement
Berkeley’s program plans to increase Software Engineering and UI Design enrollment by 500 total students/year, as well as increase the number of women and underrepresented minority CS majors by a factor of three.
Each of the selected schools brings a unique and innovative approach to addressing current scaling issues, and we are excited to collaborate in developing concrete strategies to develop sustainable and inclusive educational programs. Stay tuned over the coming year, where we will report on program recipients' progress and share results with the broader CS education community.
Announcing the Google MOOC Focused Research Awards
Monday, March 09, 2015
Posted by Maggie Johnson, Director of Education and University Relations, and Aimin Zhu, University Relations Manager, APAC
Last year, Google and
Tsinghua University
hosted the
2014 APAC MOOC Focused Faculty Workshop
, an event designed to share, brainstorm and generate ideas aimed at fostering MOOC innovation. As a result of the
ideas generated at the workshop
, we solicited proposals from the attendees for research collaborations that would advance important topics in MOOC development.
After expert reviews and committee discussions, we are pleased to announce the following recipients of the MOOC
Focused Research Awards
. These awards cover research exploring new interactions to enhance learning experience, personalized learning, online community building, interoperability of online learning platforms and education accessibility:
“MOOC Visual Analytics” - Michael Ginda, Indiana University, United States
“Improvement of students’ interaction in MOOCs using participative networks” - Pedro A. Pernías Peco, Universidad de Alicante, Spain
“Automated Analysis of MOOC Discussion Content to Support Personalised Learning” - Katrina Falkner, The University of Adelaide, Australia
“Extending the Offline Capability of Spoken Tutorial Methodology” - Kannan Moudgalya, Indian Institute of Technology Bombay, India
“Launching the Pan Pacific ISTP (Information Science and Technology Program) through MOOCs” - Yasushi Kodama, Hosei University, Japan
“Fostering Engagement and Social Learning with Incentive Schemes and Gamification Elements in MOOCs” - Thomas Schildhauer, Alexander von Humboldt Institute for Internet and Society, Germany
“Reusability Measurement and Social Community Analysis from MOOC Content Users” - Timothy K. Shih, National Central University, Taiwan
In order to further support these projects and foster collaboration, we have begun pairing the award recipients with Googlers pursuing online education research as well as product development teams.
Google is committed to supporting innovation in
online learning at scale
, and we congratulate the recipients of the MOOC Focused Research Awards. It is our belief that these collaborations will further develop the potential of online education, and we are very pleased to work with these researchers to jointly push the frontier of MOOCs.
Google Faculty Research Awards: Winter 2015
Thursday, February 19, 2015
Posted by Maggie Johnson, Director of Education and University Relations
We have just completed another round of the
Google Faculty Research Awards
, our biannual open call for research proposals on Computer Science and related topics, including systems, machine perception, structured data, robotics, and mobile. 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 808 proposals, an increase of 12% over
last round
, covering 55 countries on 6 continents. After expert reviews and committee discussions, we decided to fund 122 projects, with 20% of the funding awarded to universities outside the U.S. The subject areas that received the highest level of support were systems, human-computer interaction, and machine perception.
The Faculty Research Award program enables us to build strong relationships with faculty around the world who are pursuing innovative research, and plays an important role for Google’s
Research organization
by fostering an exchange of ideas that advances the state of the art. Each round, we receive proposals from faculty who may be just starting their careers, or who might be experimenting in new areas that help us look forward and innovate on what's emerging in the CS community.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is April 15), please visit
our website
for more information.
Announcing the 2015 North American Google PhD Fellows
Wednesday, February 18, 2015
Posted by Michael Rennaker, Google University Relations
In 2009, Google created the
PhD Fellowship program
to recognize and support outstanding graduate students doing exceptional work in Computer Science (CS) and related disciplines. In that time we’ve seen past recipients add depth and breadth to CS by developing new ideas and research directions, from
building new intelligence models
to
changing the way in which we interact with computers
to
advancing into faculty positions
, where they go on to train the next generation of researchers.
Reflecting our continuing commitment to building strong relations with the global academic community, we are excited to announce the latest North American Google PhD Fellows. The following 15 fellowship recipients were chosen from a highly competitive group, and represent the outstanding quality of nominees provided by our university partners:
Justin Meza, Google US/Canada Fellowship in Systems Reliability (Carnegie Mellon University)
Waleed Ammar, Google US/Canada Fellowship in Natural Language Processing (Carnegie Mellon University)
Aaron Parks, Google US/Canada Fellowship in Mobile Networking (University of Washington)
Kyle Rector, Google US/Canada Fellowship in Human Computer Interaction (University of Washington)
Nick Arnosti, Google US/Canada Fellowship in Market Algorithms (Stanford University)
Osbert Bastani, Google US/Canada Fellowship in Programming Languages (Stanford University)
Carl Vondrick, Google US/Canada Fellowship in Machine Perception, (Massachusetts Institute of Technology)
Wojciech Zaremba, Google US/Canada Fellowship in Machine Learning (New York University)
Xiaolan Wang, Google US/Canada Fellowship in Structured Data (University of Massachusetts Amherst)
Muhammad Naveed, Google US/Canada Fellowship in Security (University of Illinois at Urbana-Champaign)
Masoud Moshref Javadi, Google US/Canada Fellowship in Computer Networking (University of Southern California)
Riley Spahn, Google US/CanadaFellowship in Privacy (Columbia University)
Saurabh Gupta, Google US/Canada Fellowship in Computer Vision (University of California, Berkeley)
Yun Teng, Google US/Canada Fellowship in Computer Graphics (University of California, Santa Barbara)
Tan Zhang, Google US/Canada Fellowship in Mobile Systems (University of Wisconsin-Madison)
This group of students represent the next generation of researchers who endeavor to solve some of the most interesting challenges in Computer Science. We offer our congratulations, and look forward to their future contributions to the research community with high expectations.
MOOC Research and Innovation
Tuesday, December 09, 2014
Posted by Maggie Johnson, Director of Education and University Relations
Recently,
Tsinghua University
and Google collaborated to host the
2014 APAC MOOC Focused Faculty Workshop
in Shanghai, China. The workshop brought together
37 professors from 12 countries
in APAC, NA and EMEA to share, brainstorm and generate important topics that are of mutual interests in the research behind MOOCs and how to foster MOOC innovation.
During the 2-day workshop, faculty and Googlers shared lessons learned and best practices for the following focus areas:
Effectiveness of
hybrid learning
models.
Topics in adaptive learning and how they can tailor to individual students by Integrating MOOCs into a student's timetable / semester / curriculum.
Standards and practices for interoperability between online learning platforms.
Current focuses and important topics for future MOOC research.
In addition to discussing these focus areas, here was ample time for participants to brainstorm and discuss innovative research ideas for the next-steps in potential research collaboration. Emerging from these discussions were the following themes identified as important future research topics:
Adding new interactions to MOOCs including social and
gamification
Building a data & analytics Infrastructure that provides a foundation for personalized learning
Interoperability across platforms, and providing access to online content for audiences with limited access.
Google is committed to supporting research and innovation in
online learning at scale
, through both grants and our open source
Course Builder
platform, and we are excited to pursue potential research collaborations with partner universities to move forward on the topics discussed. Stay tuned for future announcements on research and collaboration aimed at enabling further MOOC innovation.
Google Research Awards: Summer 2014
Wednesday, August 20, 2014
posted by Maggie Johnson, Director of Education and University Relations
We have just completed another round of the
Google Research Awards
, our biannual open call for proposals on computer science-related topics including systems, machine perception, structured data, robotics, and mobile. 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 722 proposals, an increase of 5% over last round, covering 44 countries on 6 continents. After expert reviews and committee discussions, we decided to fund 110 projects. The subject areas that received the highest level of support were systems, human-computer interaction, mobile, and machine perception, with 22% of the funding awarded to universities outside the U.S.
We introduced three new topics this round, representing important new research areas for Google. Computational neuroscience looks at the information processing properties of the brain and nervous system. One funded proposal will study scene recognition in this context. A second new area is physical interactions with devices. With the introduction of new paradigms such as
Google Glass
, we can study how such devices expand our processing capabilities. The third new area is online learning at scale, which covers topics such as teacher-student interaction at scale, data-driven adaptive learning, and innovative assessment methods.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is October 15), please visit
our website
for more information.
Google Award Program stimulates Journalism and CS collaboration
Wednesday, February 19, 2014
Posted by Krishna Bharat, Distinguished Research Scientist
Last fall, Google invited academic researchers to participate in a Computational Journalism awards program focused on the intersection of Computer Science and Journalism. We solicited proposals for original research projects relevant to today’s fast evolving news industry.
As technology continues to shape and be shaped by the media landscape, applicants were asked to rethink traditional models and roles in the ecosystem, and reimagine the lifecycle of the news story in the online world. We encouraged them to develop innovative tools and open source software that could benefit readers and be game-changers for reporters and publishers. Each award includes funding of $60,000 in cash and $20,000 in computing credits on Google’s Cloud Platform.
We congratulate the recipients of these awards, whose projects are described below, and look forward to the results of their research. Stay tuned for updates on their progress.
Larry Birnbaum
, Professor of Electrical Engineering and Computer Science, and Journalism, Northwestern University
Project
: Thematic Characterization of News Stories
This project aims to develop computational methods for identifying abstract themes or "angles" in news stories, e.g., seeing a story as an instance of "pulling yourself up by your bootstraps," or as a "David vs. Goliath" story. In collaboration with journalism and computer science students, we will develop applications utilizing these methods in the creation, distribution, and consumption of news content.
Irfan Essa
, Professor, Georgia Institute of Technology
Project
: Tracing Reuse in Political Language
Our goal in this project is to research, and then develop a data-mining tool that allows an online researcher to find and trace language reuse. By language reuse, we specifically mean: Can we find if in a current text some language was used that can be traced back to some other text or script. The technical innovation in this project is aimed at (1) identifying linguistic reuse in documents as well as other forms of material, which can be converted to text, and therefore includes political speeches and videos. Another innovation will be in (2) how linguistic reuse can be traced through the web and online social networks.
Susan McGregor
, Assistant Director, Tow Center for Digital Journalism, Columbia Journalism School
Project
: InfoScribe
InfoScribe
is a collaborative web platform that lets citizens participate in investigative journalism projects by digitizing select data from scanned document sets uploaded by journalists. One of InfoScribe's primary research goals is to explore how community participation in journalistic activities can help improve their accuracy, transparency and impact. Additionally, InfoScribe seeks to build and expand upon understandings of how computer vision and statistical inference can be most efficiently combined with human effort in the completion of complex tasks.
Paul Resnick
, Professor, University of Michigan School of Information
Project
: RumorLens
RumorLens
is a tool that will aid journalists in finding posts that spread or correct a particular rumor on Twitter, by exploring the size of the audiences that those posts have reached. In the collection phase, the user provides one or a few exemplar tweets and then manually classifies a few hundred others as spreading the rumor, correcting it, or labeling it as unrelated. This enables automatic retrieval and classification of remaining tweets, which are then presented in an interactive visualization that shows audience sizes.
Ryan Thornburg
, Associate Professor, School of Journalism and Mass Communication, University of North Carolina at Chapel Hill
Project: Public Records Dashboard for Small Newsrooms
Building off our Knight News Challenge effort to bring data-driven journalism to readers of rural newspaper websites, we are developing an internal newsroom tool that will alert reporters and editors to potential story tips found in public data. Our project aims to lower the cost of finding in public data sets stories that shine light in dark places, hold powerful people accountable, and explain our increasingly complex and interconnected world. (Public facing site for the data acquisition element of the project at
http://open-nc.org
)
Google Research Awards: Winter 2014
Tuesday, February 18, 2014
Posted by Maggie Johnson, Director of Education & University Relations
We have just completed another round of the
Google Research Awards
, our biannual open call for proposals on computer science-related topics including robotics, natural language processing, systems, policy, and mobile. 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 691 proposals, an increase of 19% over last round, covering 46 countries on 6 continents. After expert reviews and committee discussions, we decided to fund 115 projects. The subject areas that received the highest level of support were human-computer interaction, systems, and machine learning, with 25% of the funding awarded to universities outside the U.S.
We set a new record this round with over 2000 reviews done by 650 reviewers. Each proposal is reviewed by internal committees who provide feedback on merit and relevance. In many cases, the committees include some of the foremost experts in the world. All committee members are volunteers who spend a significant amount of time making the Research Award program happen twice a year.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is April 15), please visit
our website
for more information.
New Research Challenges in Language Understanding
Friday, November 22, 2013
Posted by Maggie Johnson, Director of Education and University Relations
We held the first global Language Understanding and Knowledge Discovery Focused Faculty Workshop in Nanjing, China, on November 14-15, 2013. Thirty-four faculty members joined the workshop arriving from 10 countries and regions across APAC, EMEA and the US. Googlers from Research, Engineering and University Relations/University Programs also attended the event.
The 2-day workshop included keynote talks, panel discussions and break-out sessions [
agenda
]. It was an engaging and productive workshop, and we saw lots of positive interactions among the attendees. The workshop encouraged communication between Google and faculty around the world working in these areas.
Research in text mining continues to explore open questions relating to entity annotation, relation extraction, and more. The workshop’s goal was to brainstorm and discuss relevant topics to further investigate these areas. Ultimately, this research should help provide users search results that are much more relevant to them.
At the end of the workshop, participants identified four topics representing challenges and opportunities for further exploration in Language Understanding and Knowledge Discovery:
Knowledge representation, integration, and maintenance
Efficient and scalable infrastructure and algorithms for inferencing
Presentation and explanation of knowledge
Multilingual computation
Going forward, Google will be collaborating with academic researchers on a position paper related to these topics. We also welcome faculty interested in contributing to further research in this area to submit a proposal to the
Faculty Research Awards program
. Faculty Research Awards are one-year grants to researchers working in areas of mutual interest.
The faculty attendees responded positively to the focused workshop format, as it allowed time to go in depth into important and timely research questions. Encouraged by their feedback, we are considering similar workshops on other topics in the future.
Google Research Awards: Summer 2013
Monday, August 12, 2013
Posted by Maggie Johnson, Director of Education & University Relations
Another round of the
Google Research Awards
is complete. This is our biannual open call for proposals on computer science-related topics including machine learning and structured data, policy, human computer interaction, and geo/maps. Our grants cover tuition for a graduate student and provide both faculty and students the opportunity to work directly with Google scientists and engineers.
This round, we received 550 proposals from 50 countries. After expert reviews and committee discussions, we decided to fund 105 projects. The subject areas that received the highest level of support were human-computer interaction, systems and machine learning. In addition, 19% of the funding was awarded to universities outside the U.S.
We noticed some new areas emerging in this round of proposals. In particular, an increase of interest in neural networks, accessibility-related projects, and some innovative ideas in robotics. One project features the use of
Android-based
multi-robot systems which are significantly more complex than single robot systems. Faculty researchers are looking to explore novel uses of
Google Glass
such as an indoor navigation system for blind users, and how Glass can facilitate social interactions.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is October 15), please visit
our website
for more information.
Natural Language Understanding-focused awards announced
Tuesday, July 02, 2013
Posted by Massimiliano Ciaramita, Research Scientist and David Harper, Head University Relations (EMEA)
Some of the biggest challenges for the scientific community today involve understanding the principles and mechanisms that underlie natural language use on the Web. An example of long-standing problem is language ambiguity; when somebody types the word “Rio” in a query do they mean the city, a movie, a casino, or something else? Understanding the difference can be crucial to help users get the answer they are looking for. In the past few years, a significant effort in industry and academia has focused on disambiguating language with respect to Web-scale knowledge repositories such as Wikipedia and Freebase. These resources are used primarily as canonical, although incomplete, collections of “entities”. As entities are often connected in multiple ways, e.g., explicitly via hyperlinks and implicitly via factual information, such resources can be naturally thought of as (knowledge) graphs. This work has provided the first breakthroughs towards anchoring language in the Web to interpretable, albeit initially shallow, semantic representations. Google has brought the vision of semantic search directly to millions of users via the adoption of the
Knowledge Graph
. This massive change to search technology has also been called a shift “from strings to things”.
Understanding natural language is at the core of Google's work to help people get the information they need as quickly and easily as possible. At Google we work hard to advance the state of the art in natural language processing, to improve the understanding of fundamental principles, and to solve the algorithmic and engineering challenges to make these technologies part of everyday life. Language is inherently productive; an infinite number of meaningful new expressions can be formed by combining the meaning of their components systematically. The logical next step is the semantic modeling of structured meaningful expressions -- in other words, “what is said” about entities. We envision that knowledge graphs will support the next leap forward in language understanding towards scalable compositional analyses, by providing a universe of entities, facts and relations upon which semantic composition operations can be designed and implemented.
So we’ve just awarded over $1.2 million to support several natural language understanding research awards given to university research groups doing work in this area. Research topics range from semantic parsing to statistical models of life stories and novel compositional inference and representation approaches to modeling relations and events in the Knowledge Graph.
These awards went to researchers in nine universities and institutions worldwide, selected after a rigorous internal review:
Mark Johnson and Lan Du (Macquarie University) and Wray Buntine (NICTA) for “Generative models of Life Stories”
Percy Liang and Christopher Manning (Stanford University) for “Tensor Factorizing Knowledge Graphs”
Sebastian Riedel (University College London) and Andrew McCallum (University of Massachusetts, Amherst) for “Populating a Knowledge Base of Compositional Universal Schema”
Ivan Titov (University of Amsterdam) for “Learning to Reason by Exploiting Grounded Text Collections”
Hans Uszkoreit (Saarland University and DFKI), Feiyu Xu (DFKI and Saarland University) and Roberto Navigli (Sapienza University of Rome) for “Language Understanding cum Knowledge Yield”
Luke Zettlemoyer (University of Washington) for “Weakly Supervised Learning for Semantic Parsing with Knowledge Graphs”
We believe the results will be broadly useful to product development and will further scientific research. We look forward to working with these researchers, and we hope we will jointly push the frontier of natural language understanding research to the next level.
2013 Google PhD Fellowships: 5 Years of Supporting the Future of Computer Science
Tuesday, June 11, 2013
Posted by Michael Rennaker, Google University Relations
We are extremely excited to announce the
2013 Global Google PhD Fellows
. From all around the globe, these 39 PhD students represent the fifth class in the program’s history, a select group recognized by Google researchers and their institutions as some of the most promising young academics in the world. As we welcome the newest class of PhD Fellows, we take a look back at the program’s roots and hear from two past recipients.
In 2009, Google launched its
PhD Fellowship Program
, created to recognize and support outstanding graduate students pursuing work in computer science, related disciplines or promising research areas. In its inaugural year, 13 United States PhD students were awarded fellowships, drawn from an extremely competitive pool of applicants. The global program now covers Europe, China, India and Australia and continues to draw some of the best young researchers, reflecting Google’s commitment to building strong relations with the academic community.
Among those first recipients of the fellowship award are 2009 PhD Fellow
Roxana Geambasu
, Visiting Professor in the
Computer Science Department
at Columbia University, and 2010 European Doctoral Fellow
Roland Angst
, Visiting Assistant Professor at Stanford University and affiliated with the
Max Planck Center for Visual Computing and Communication
. As early recipients of the award, Roxana and Roland reflect on the impact that the Google Fellowship program had on their careers.
For Roxana, the fellowship provided the tools and connections that helped lay the foundation for her academic career. She believes industrial fellowship programs are very important, as they give students an opportunity to interact more closely with industry.
“Beyond the financial support, I think that the fellowship impacted my career in many important ways. First, the Google fellowships are regarded as highly competitive, so receiving the award was probably a big plus on my resume when I was interviewing for faculty positions.”
“Second, the award yielded a mentor within Google, Brad Chen, with whom I've kept in touch ever since, as well as opportunities to visit the campus, deliver talks and meet Google engineers. Brad and I continue to meet at conferences and discuss my work, his work and (of late) the work of my students; it’s through that relationship I’m exposed to new people from Google and gain valuable advice about
faculty award opportunities
.”
Roland Angst credits the award with the ability to lighten his teaching load and instead focus on his research, which ultimately prepared him for his future academic career. Like Roxanna, Roland states that the fellowship also gave him the opportunity to establish connections with people working in related topics in industry.
“In my view, programs such as the Google Fellowship Awards represent an important and integral link between industry and universities. Firstly, such programs increase the awareness in the academic world for relevant problems in industry. Secondly, these programs allow the IT industry to express their gratitude to the educational services provided by the universities on which the IT industry heavily relies on."
We welcome the latest recipients of the Global Google PhD Fellowships for 2013 with great excitement and high expectations. Recognized for their incredible innovation, creativity and leadership, we are very happy to support these excellent PhD students and offer our sincere congratulations.
Education Awards on Google App Engine
Wednesday, March 27, 2013
Posted by Andrea Held, Google University Relations
Cross-posted with
Google Developers Blog
Last year we
invited
proposals for innovative projects built on Google’s infrastructure. Today we are pleased to announce the 11 recipients of a
Google App Engine Education Award
. Professors and their students are using the award in cloud computing courses to study databases, distributed systems, web mashups and to build educational applications. Each selected project received $1000 in Google App Engine credits.
Awarding computational resources to classroom projects is always gratifying. It is impressive to see the creative ideas students and educators bring to these programs.
Below is a brief introduction to each project. Congratulations to the recipients!
John David N. Dionisio
, Loyola Marymount University
Project description
: The objective of this undergraduate database systems course is for students to implement one database application in two technology stacks, a traditional relational database and on Google App Engine. Students are asked to study both models and provide concrete comparison points.
Xiaohui (Helen) Gu
, North Carolina State University
Project description
:
Advanced Distributed Systems Class
The goal of the project is to allow the students to learn distributed system concepts by developing real distributed system management systems and testing them on real world cloud computing infrastructures such as Google App Engine.
Shriram Krishnamurthi
, Brown University
Project description
:
WeScheme
is a programming environment that runs in the Web browser and supports interactive development. WeScheme uses App Engine to handle user accounts, serverside compilation, and file management.
Feifei Li
, University of Utah
Project description
: A graduate-level course that will be offered in Fall 2013 on the design and implementation of large data management system kernels. The objective is to integrate features from a relational database engine with some of the new features from NoSQL systems to enable efficient and scalable data management over a cluster of commodity machines.
Mark Liffiton
, Illinois Wesleyan University
Project description
:
TeacherTap
is a free, simple classroom-response system built on Google App Engine. It lets students give instant, anonymous feedback to teachers about a lecture or discussion from any computer or mobile device with a web browser, facilitating more adaptive class sessions.
Eni Mustafaraj
, Wellesley College
Project description
: Topics in Computer Science: Web Mashups. A CS2 course that combines Google App Engine and MIT App Inventor. Students will learn to build apps with App Inventor to collect data about their life on campus. They will use Google App Engine to build web services and apps to host the data and remix it to create web mashups. Offered in the 2013 Spring semester.
Manish Parashar
, Rutgers University
Project description
: Cloud Computing for Scientific Applications -- Autonomic Cloud Computing teaches students how a hybrid HPC/Grid + Cloud cyber infrastructure can be effectively used to support real-world science and engineering applications. The goal of our efforts is to explore application formulations, Cloud and hybrid HPC/Grid + Cloud infrastructure usage modes that are meaningful for various classes of science and engineering application workflows.
Orit Shaer
, Wellesley College
Project description
:
GreenTouch
GreenTouch is a collaborative environment that enables novice users to engage in authentic scientific inquiry. It consists of a mobile user interface for capturing data in the field, a web application for data curation in the cloud, and a tabletop user interface for exploratory analysis of heterogeneous data.
Elliot Soloway
, University of Michigan
Project description
: WeLearn Mobile Platform: Making Mobile Devices Effective Tools for K-12. The platform makes mobile devices (Android, iOS, WP8) effective, essential tools for all-the-time, everywhere learning. WeLearn’s suite of productivity and communication apps enable learners to work collaboratively; WeLearn’s portal, hosted on Google App Engine, enables teachers to send assignments, review, and grade student artifacts. WeLearn is available to educators at no charge.
Jonathan White
, Harding University
Project description
: Teaching Cloud Computing in an Introduction to Engineering class for freshmen. We explore how well-designed systems are built to withstand unpredictable stresses, whether that system is a building, a piece of software or even the human body. The grant from Google is allowing us to add an overview of cloud computing as a platform that is robust under diverse loads.
Dr. Jiaofei Zhong
, University of Central Missouri
Project description
: By building an online Course Management System, students will be able to work on their team projects in the cloud. The system allows instructors and students to manage the course materials, including course syllabus, slides, assignments and tests in the cloud; the tool can be shared with educational institutions worldwide.
Our Commitment to Social Computing Research: Social Interactions Focused Awards Announcement
Tuesday, March 12, 2013
Ed H. Chi, Staff Research Scientist
Social interactions have always been an important part of the human experience. Social interaction research has shown results ranging from
influences on our behavior from social networks
[Aral2012] to
our understanding of social belonging on health
[Walton2011], as well as
how conflicts and coordination play out in Wikipedia
[Kittur2007]. Interestingly, social scientists have studied social interactions for many years, but it wasn’t until very recently that researchers can study these mechanisms through the explosion of services and data available on web-based social systems.
From information dissemination and the spread of innovation and ideas, to scientific discovery, we are seeing how a deep understanding of social interactions is affecting many different fields, such as health and education. For instance, scientists now have strong evidence that
social interactions underlie many fundamental learning mechanisms
starting from infancy well into adulthood [Meltzoff2009], and that
peer discussions are critical in conceptual learning in college classes
[Smith2009]. How might these learning science findings be built into social systems and products so that users maximize what they learn on the Web?
We know that interactions on the Web are diverse and people-centered. Google now enables social interactions to occur across many of our products, from
Google+
to Search to
YouTube
. To understand the future of this socially connected web, we need to investigate fundamental patterns, design principles, and laws that shape and govern these social interactions.
We envision research at the intersection of disciplines including Computer Science, Human-Computer Interaction (HCI), Social Science, Social Psychology, Machine Learning, Big Data Analytics, Statistics and Economics. These fields are central to the study of how social interactions work, particularly driven by new sources of data, for example, open data sets from Web2.0 and social media sites, government databases, crowdsourcing, new survey techniques, and crisis management data collections. New techniques from network science and computational modeling, social network and sentiment analysis, application of statistical and machine learning, as well as theories from evolutionary theory, physics, and information theory, are actively being used in social interaction research.
We’re pleased to announce that Google has awarded over $1.2 million dollars to support the Social Interactions Research Awards, which are given to university research groups doing work in social computing and interactions. Research topics range from crowdsourcing, social annotations, a social media behavioral study, social learning, conversation curation, and scientific studies of how to start online communities.
We have awarded 15 researchers in 7 universities. We selected these proposals after a rigorous internal review. We believe the results will be broadly useful to product development and will further scientific research.
Joseph Konstan, Loren Terveen, and John Riedl from University of Minnesota. Precision Crowdsourcing: Closing the Loop to turn Information Consumers into Information Contributors.
Mor Naaman from Rutgers University, and Oded Nov from Polytechnic Institute of New York University. Examining the Impact of Social Traces on Page Visitors’ Opinions and Engagement.
Paul Resnick, Eytan Adar, and Cliff Lampe from University of Michigan. MTogether: A Living Lab for Social Media Research.
Marti Hearst from UC Berkeley. Understanding Social Learning Among Subgroups Within Large Online Learning Environments.
David Karger and Rob Miller from MIT. Crowdsourced Curation of Conversations.
Robert Kraut, Laura Dabbish, Jason Hong, Aniket Kittur from CMU. Successfully Starting Online Groups.
We look forward to working with these researchers, and we hope that we will jointly push the frontier of social interactions research to the next level.
References
[1] Aral, S., & Walker, D. (2012). Identifying Influential and Susceptible Members of Social Networks. Science , 337 (6092 ), 337–341. doi:10.1126/science.1215842
[2] Walton, G. M., & Cohen, G. L. (2011). A Brief Social-Belonging Intervention Improves Academic and Health Outcomes of Minority Students. Science , 331 (6023 ), 1447–1451. doi:10.1126/science.1198364
[3] Aniket Kittur, Bongwon Suh, Bryan Pendleton, Ed H. Chi.
He Says, She Says: Conflict and Coordination in Wikipedia
. In Proc. of ACM Conference on Human Factors in Computing Systems (CHI2007), pp. 453--462, April 2007. ACM Press. San Jose, CA.
[4] Meltzoff, A. N., Kuhl, P. K., Movellan, J., & Sejnowski, T. J. (2009). Foundations for a New Science of Learning. Science , 325 (5938), 284–288. doi:10.1126/science.1175626
[5] Smith, M. K., Wood, W. B., Adams, W. K., Wieman, C., Knight, J. K., Guild, N., & Su, T. T. (2009). Why Peer Discussion Improves Student Performance on In-Class Concept Questions. Science , 323 (5910), 122–124. doi:10.1126/science.1165919
Google Research Awards: Winter, 2013
Friday, February 22, 2013
Posted by Maggie Johnson, Director of Education & University Relations
Another round of the
Google Research Awards
has just been completed. This is our bi-annual open call for proposals on a variety of computer science-related topics, including systems, machine perception, natural language processing, security and many others. Our grants cover tuition and travel for a graduate student and provides faculty and students the opportunity to work directly with Google scientists and engineers.
This round, we received almost 600 proposals from 46 different countries. After expert reviews and committee discussions, we decided to fund 102 projects. The subject areas that received the highest level of support were human-computer interaction, machine learning, and mobile. In addition, 22% of the funding was awarded to universities outside the U.S.
Google’s
University Relations
funding falls into three categories. The first is the Google Research Award program which funds new faculty and innovative projects, or helps faculty get a new research program off the ground. We fund over 200 projects annually through this program. We feel this is a great way for Google to support a large number of faculty and projects, and it helps us keep a pulse on what’s going on in academic computer science research.
The second category of funding goes toward more
focused, longer-term projects
, where we collaborate closely on projects of mutual interest. Our
PhD Fellowship program
is also a part of our focused program strategy. The third category goes toward new programs and initiatives, and to the development of research and education in emerging countries.
Congratulations to the well-deserving
recipients of this round’s awards
. If you are interested in applying for the next round (deadline is April 15), please visit
our website
for more information.
Millions of Core-Hours Awarded to Science
Monday, December 17, 2012
Posted by Andrea Held, Program Manager, University Relations
In 2011 Google University Relations
launched
a new academic research awards program,
Google Exacycle for Visiting Faculty
, offering up to one billion core-hours to qualifying proposals. We were looking for projects that would consume 100M+ core-hours each and be of critical benefit to society. Not surprisingly, there was no shortage of applications.
Since then, the following seven scientists have been working on-site at Google offices in Mountain View and Seattle. They are here to run large computing experiments on Google’s infrastructure to change the future. Their projects include exploring antibiotic drug resistance, protein folding and structural modelling, drug discovery, and last but not least, the dynamic universe.
Today, we would like to introduce the Exacycle award recipients and their work. Please stay tuned for updates next year.
Simulating a Dynamic Universe with the Large Synoptic Sky Survey
Jeff Gardner
, University of Washington, Seattle, WA
Collaborators:
Andrew Connolly
, University of Washington, Seattle, WA, and
John Peterson
, Purdue University, West Lafayette, IN
Research subject
:
The Large Synoptic Survey Telescope
(LSST) is one of the most ambitious astrophysical research programs ever undertaken. Starting in 2019, the LSST’s 3.2 Gigapixel camera will repeatedly survey the southern sky, generating tens of petabytes of data every year. The images and catalogs from the LSST have the potential to transform both our understanding of the universe and the way that we engage in science in general.
Exacycle impact
: In order to design the telescope to yield the best possible science, the LSST collaboration has undertaken a formidable computational campaign to simulate the telescope itself. This will optimize how the LSST surveys the sky and provide realistic datasets for the development of analysis pipelines that can operate on hundreds of petabytes. Using Exacycle, we are reducing the time required to simulate one night of LSST observing, roughly 5 million images, from 3 months down to a few days. This rapid turnaround will enable the LSST engineering teams to test new designs and new algorithms with unprecedented precision, which will ultimately lead to bigger and better science from the LSST.
Designing and Defeating Antibiotic Drug Resistance
Peter Kasson, Assistant Professor, Departments of Molecular Physiology and Biological Physics and of Biomedical Engineering, University of Virginia
Research subject
: Antibiotics have made most bacterial infections routinely treatable. As antibiotic use has become common, bacterial resistance to these drugs has also increased. Recently, some bacteria have arisen that are resistant to almost all antibiotics. We are studying the basis for this resistance, in particular the enzyme that acts to break down many antibiotics. Identifying the critical changes required for pan-resistance will aid surveillance and prevention; it will also help elucidate targets for the development of new therapeutic agents.
Exacycle impact
: Exacycle allows us to simulate the structure and dynamics of several thousand enzyme variants in great detail. The structural differences between enzymes from resistant and non-resistant bacteria are subtle, so we have developed methods to compare structural "fingerprints" of the enzymes and identify distinguishing characteristics. The complexity of this calculation and large number of potential bacterial sequences mean that this is a computationally intensive task; the massive computing power offered by Exacycle in combination with some novel sampling strategies make this calculation tractable.
Sampling the conformational space of G protein-coupled receptors
Kai Kohlhoff, Research Scientist at Google
Collaborators: Research labs of
Vijay Pande
and
Russ Altman
at Stanford University
Research subject
: G protein-coupled receptors (
GPCRs
) are proteins that act as signal transducers in the cell membrane and influence the response of a cell to a variety of external stimuli. GPCRs play a role in many human diseases, such as asthma and hypertension, and are well established as a primary drug target.
Exacycle impact
: Exacycle let us perform many tens of thousands of molecular simulations of membrane-bound GPCRs in parallel using the
Gromacs
software. With
MapReduce
,
Dremel
, and other technologies, we analyzed the 100s of Terabytes of generated data and built
Markov State Models
. The information contained in these models can help scientists design drugs that have higher potency and specificity than those presently available.
Results
: Our models let us explore kinetically meaningful receptor states and transition rates, which improved our understanding of the structural changes that take place during activation of a signaling receptor. In addition, we used Exacycle to study the affinity of drug molecules when binding to different receptor states.
Modeling transport through the nuclear pore complex
Daniel Russel, post doc in structural biology, University of California, San Francisco
Research subject
: Our goal is to develop a predictive model of transport through the nuclear pore complex (NPC). Developing the model requires understanding how the behavior of the NPC varies as we change the parameters governing the components of the system. Such a model will allow us to understand how transportins, the unstructured domains and the rest of the cellular milieu, interact to determine efficiency and specificity of macromolecular transport into and out of the nucleus.
Exacycle impact
: Since data describing the microscopic behavior of most parts of the nuclear transport process is incomplete and contradictory, we have to explore a larger parameter space than would be feasible with traditional computational resources.
Status
: We are currently modeling various experimental measurements of aspects of the nuclear transport process. These experiments range from simple ones containing only a few components of the transport process to measurements on the whole nuclear pore with transportins and cellular milieu.
Large scale screening for new drug leads that modulate the activity of disease-relevant proteins
James Swetnam, Scientific Software Engineer, drugable.org, NYU School of Medicine
Collaborators: Tim Cardozo, MD, PhD - NYU School of Medicine.
Research subject
: We are using a high throughput, CPU-bound procedure known as virtual ligand screening to ‘dock’, or produce rough estimates of binding energy, for a large sample of bioactive chemical space to the entirety of known protein structures. Our goal is the first computational picture of how bioactive chemistry with therapeutic potential can affect human and pathogen biology.
Exacycle Impact
: Typically, using our academic lab’s resources, we could screen a few tens of thousands of compounds against a single protein to try to find modulators of its function. To date, Exacycle has enabled us to screen 545,130 compounds against 8,535 protein structures that are involved in important and underserved diseases as cancer, diabetes, malaria, and HIV to look for new leads towards future drugs.
Status
: We are currently expanding our screens to an additional 206,190 models from
ModBase. We aim to have a public dataset for the research community in the first half of 2013.
Protein Structure Prediction and Design
Michael Tyka, Research Fellow, University of Washington, Seattle, WA
Research subject
: The precise relationship between the primary sequence and the
three dimensional structure of proteins
is one of the unsolved grand challenges of computational biochemistry. The
Baker Lab
has made significant progress in recent years by developing more powerful protein prediction and design algorithms using the
Rosetta Protein Modelling suite
.
Exacycle impact
: Limitations in the accuracy of the
physical model
and lack of sufficient computational power have prevented solutions to broader classes of medically relevant problems. Exacycle allows us to improve model quality by conducting large parameter optimization sweeps with a very large dataset of experimental protein structural data. The improved energy functions will benefit the entire theoretical protein research community.
We are also using Exacycle to conduct simultaneous
docking
and
one-sided protein design
to develop novel protein binders for a number of medically relevant targets. For the first time, we are able to aggressively redesign backbone conformations at the binding site. This allows for a much greater flexibility in possible binding shapes but also hugely increases the space of possibilities that have to be sampled. Very promising designs have already been found using this method.
Continuing the quest for future computer scientists with CS4HS
Thursday, December 13, 2012
Erin Mindell, Program Manager, Google Education
Computer Science for High School (CS4HS) began five years ago with a simple question: How can we help create a much needed influx of CS majors into universities and the workforce? We took our questions to three of our university partners--University of Washington, Carnegie Mellon, and UCLA--and together we came up with CS4HS. The model was based on a “train the trainer” technique. By focusing our efforts on teachers and bringing them the skills they need to implement CS into their classrooms, we would be able to reach even more students. With grants from Google, our partner universities created curriculum and put together hands-on, community-based workshops for their local area teachers.
Since the initial experiment, CS4HS has exploded into a worldwide program, reaching more than 4,000 teachers and 200,000 students either directly or indirectly in more than 34 countries. These hands-on, in-person workshops are a hallmark of our program, and we will continue to fund these projects going forward. (For information on
how to apply
, please see our
website
.) The success of this popular program speaks for itself, as we receive more quality proposals each year. But success comes at a price, and we have found that the current format of the workshops is not infinitely scalable.
This is where Research at Google comes in. This year, we are experimenting with a new model for CS4HS workshops. By harnessing the success of online courses such as
Power Searching with Google
, and utilizing open-source platforms like the one found in
Course Builder
, we are hoping to put the
“M” in “MOOC”
and reach a broader audience of educators, eager to learn how to teach CS in their classrooms.
For this pilot, we are looking to sponsor two online workshops, one that is geared toward CS teachers, and one that is geared toward CS for non-CS teachers to go live in 2013. This is a way for a university (or several colleges working together) to create one incredible workshop that has the potential to reach thousands of enthusiastic teachers. Just as with our in-person workshops, applications will be open to college, university, and technical schools of higher learning only, as we depend on their curriculum expertise to put together the most engaging programs. For this pilot, we will be looking for MOOC proposals in the US and Canada only.
We are really excited about the possibilities of this new format, and we are looking for quality applications to fund. While applications don’t have to run on our
Course Builder platform
, we may be able to offer some additional support to funded projects that do. If you are interested in joining our experiment or just learning more, you can find information on how to apply on our
CS4HS website
(or click
here
).
Applications are open until February 16, 2013; we can’t wait to see what you come up with. If you have questions, please email us at
cs4hs@google.com
.
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