Google Research Blog
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Google's Research Awards Program Update
Tuesday, July 14, 2009
Posted by Posted by Juan E. Vargas, University Relations
When we think about innovation, it is easy to forget that it took about 55 years to spread automobile usage to 1/4 of the US population, ... 35 years for the telephone, ... 20 years for the radio, ... 15 years for the PC, ... 10 years for the cell phone, ... 7 years for the Internet (Council of Competiveness,
Recognizing that innovation holds the key to many of the unique technical challenges we face, we remain committed to maintaining strong relations with the academic research community. Our Research Awards Program has experienced phenomenal growth. Of the total number of applications that we received since the program's inception in 2005, more than half were submitted in the past year. To cope with the increased level of interest worldwide, we reorganized the program to accept submissions three times per year: April 15th, August 15th, and December 15th. Proposals are evaluated by teams of engineers and researchers, who make recommendations for funding. We try to move fast. Investigators receive a response about three months after their submission.
Here are some highlights from a recent round of applications:
"Recognition and Modeling of Objects from Street View Scans of Cities"
, Princeton University
Professor Funkhouser aims to develop methods for automatic construction of semantically-labeled, detailed, and photorealistic 3D models of cities from Street View data. The main efforts will be towards the segmentation and recognition of small objects (e.g. mailboxes, fire hydrants, parking meters, etc.) in Lidar data based on shape classification and contextual reasoning. A second objective will be to construct seamless, photorealistic 3D models of complete cities by extracting and fitting parts from repositories of polygonal models.
"An Ad Auctions Trading Agent Competition"
, University of Michigan
The University of Michigan will introduce and operate a new game in the Trading Agent Competition (TAC) series of research competitions, in the domain of sponsored search. The TAC Ad Auctions (TAC/AA) game challenges participants to develop bidding strategies for advertisers in a simulated retail home entertainment market. The aim is to spur research and generate insights about advertiser bidding strategy, in a scenario more complex than those considered in the research literature to date. The TAC/AA environment features multiple interrelated keywords, a structured search user model, rich data availability, and a dynamic market context. Since 2000, the annual TAC series has catalyzed research on trading agent design and analysis, produced by a diverse group of researchers from academia and industry.
"A Suite of Automated Tools for Efficient Management and Search in Web-based Arabic Documents"
, Birzeit University, Palestine.
This research aims to design text mining and processing tools that are able to efficiently index, process, search, and categorize large quantities of Arabic data. This research addresses the challenges Arabic poses for NLP and information retrieval, automatic Arabic document categorization, root extraction, language detection, and Arabic query correction, suggestion and expansion. The PIs employ a statistical/Corpus-based approach based on contemporary data initially obtained from a local newspaper.
"When Children Search: Understanding what they do and what they could do with Google Search"
, University of Maryland
Children ages 5-13 are among the most frequent users of the Internet; yet, searching and browsing the web can present many challenges. Spelling, typing, query formulation, and deciphering results are all barriers for children in attempting to find the information they need. Professor Druin is trying to understand these issues in more diverse ages of children by focusing on current and ubiquitous search tools, namely, keyword-based web search engines.
"An Educational Camera for Kids"
, Columbia University
Professor Nayar is desiging a novel digital camera that could be used as an innovative educational medium. His target audience is students between the ages of 10 and 13 years living in poor communities across the globe. The camera, named “Bigshot,” will be presented to students as a kit to expose them to diverse science and engineering concepts. Once assembled, the camera will be used so that students can share their photos with students in other cultures using Picasa and Google Groups.
"Discovering semantic concepts and their relations in large image collections"
, Technische Unversitat Darmstadt, Germany
Professor Schiele will investigate to what extent meaningful structures can be discovered from large sets of images both in a fully unsupervised fashion as well with minimal human supervision. To this end, Professor Schiele's work will try to first discover structure and learn multi-feature distance metrics in large collections of images and then to enrich such structure by weak annotations in order to link discovered structure and to derive semantic concepts.
"Dataspace Metrics: Measuring Progress for Pay-as-you-go Information Integration"
, University of California
The goal of this project is to develop a measurement framework for gauging progress in terms of the quality and accuracy of information integration. The starting point is the development of a set of metrics for judging the “goodness’ of information integration across a number of information types and use cases. These metrics will then be analyzed and where possible, unified, so that a more general measurement framework can be developed. Such a framework will serve as a key component for future Dataspace management systems, and could provide a grounding for other collaborative information integration solutions.
For more information about this program, including submission guidelines, please visit the
Research Awards Program
Adaptive Data Analysis
Automatic Speech Recognition
Electronic Commerce and Algorithms
Google Cloud Platform
Google Play Apps
Google Science Fair
Google Voice Search
High Dynamic Range Imaging
Internet of Things
Natural Language Processing
Natural Language Understanding
Optical Character Recognition
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