Google Fellowships, the Nuts and Bolts

Posted by Leslie Yeh Johnson, Google University Relations

As you may have read, today we announced the recipients of the 2009 Google Fellowships. (You can read the announcement over on the Official Google Blog.) This is fantastic news, and the blog post makes the Google Fellowship Program sound very polished. But the truth is there was a lot more work (and scrambling) done in the background...here's a quick snapshot.

We first conceived of the idea of the fellowships late last year. Google already funds academic research through the Google Research Awards, but we really wanted to support the graduate students who are doing a lot of the research and are the future of their respective fields. Idea: why don't we search out the best and brightest PhD students and pay their tuition and expenses, plus give them an Android phone and hook them up with a Google researcher so we can all share really cool ideas? Done and done.

After we made the decision to do the fellowships in 2009, we were in for some hard work. We quickly spread the word about the fellowships in order to give the universities and students time to prepare and send us information about themselves and their research. The nominated students were doing research on a vast array of subjects: Cloud Computing, Computer Graphics, Market Algorithms, Machine Learning, Natural Language Processing, Social Computing, Information Retrieval, Compilers, and Computer Vision to name a few. I relied upon a small army of research scientists and distinguished engineers to help me review them. In addition to lending their scientific expertise to looking over the Google Research Awards, not to mention their "day job", the forty-five Googlers also were able to provide feedback on the students in record time - these guys are champs. Then a whirlwind review with Alfred Spector, VP of Research and Special Initiatives at Google, and just six months later we are proud to announce the 2009 Google Fellowship recipients.

It was a jam-packed 6 months, and I'm really proud of how the program turned out this year. That said, I'm already looking forward to our sophomore year in 2010. You should expect to see a broader program covering more areas of research, more schools, and more geographies. I can't wait.

The best and the brightest

Posted by Leslie Yeh Johnson, Google University Relations

[Also posted on the Official Google Blog]

I can't think of a better environment than academia for asking hard questions and trying to solve the unsolvable. It's at universities that graduate students perform some of the most exciting and game-changing research in computer science and technology. These university labs foster the students that are going to be the next innovators and leaders in research.

We started the Google Fellowship Program this year to support graduate students in their quest to discover and achieve great things. Our goal was to find the best and brightest PhD students and award them a unique fellowship that highlights their contributions to research and supports them through their graduate studies. Several top universities submitted their students for consideration by research scientists, distinguished engineers and executives at Google. The breadth of research covered by these students and the scope of their vision was astounding. Learning about them was exciting; choosing from among them was truly difficult.

After careful review, we are proud to announce the 2009 Google Fellowship recipients:

• Roxana Geambasu, Google Fellowship in Cloud Computing (University of Washington)
• Michael Piatek, Google Fellowship in Computer Networking (University of Washington)
• David Sontag, Google Fellowship in Machine Learning (Massachusetts Institute of Technology)
• Ali Farhadi, Google Fellowship in Computer Vision Image Interpretation (University of Illinois at Urbana-Champaign)
• Nicholas Chen, Google Fellowship in Human-Computer Interaction (University of Maryland)
• Siddhartha Sen, Google Fellowship in Fault Tolerant Computing (Princeton University)
• Ryan Peterson, Google Fellowship in Distributed Systems (Cornell University)
• Eric Gilbert, Google Fellowship in Social Computing (University of Illinois at Urbana-Champaign)
• Micha Elsner, Google Fellowship in Natural Language Processing (Brown University)
• Subhransu Maji, Google Fellowship in Computer Vision Object Recognition (University of California, Berkeley)
• Nicolas Lambert, Google Fellowship in Market Algorithms (Stanford University)
• Han Liu, Google Fellowship in Statistics (Carnegie Mellon University)
• Lixia Liu, Google Fellowship in Compiler Technology (Purdue University)

These students exemplify excellence in all areas, and we look forward to the impact that they are sure to have on their fields and the world. The Google Fellowship will provide them with funding to cover their tuition and expenses, plus an Android-powered phone and a Google mentor. Our sincere congratulations to all of them!

ACM Multimedia 2009 Grand Challenges

Posted by Jay Yagnik, Head of Computer Vision Research

At Google Research we interact with the academic research community closely through various programs like Research Awards, Visiting Faculty Program, and by active participation in various conferences. Dealing with large quantities of data gives us some unique challenges and perspectives on various problems. In many cases entirely new problem classes begin to emerge. These problems often have not received attention from a broad part of the research community. In an effort to bridge this gap for multimedia problems, we participated in setting Grand Challenges for this year's ACM Multimedia Conference. We proposed "Robust, As-Accurate-As-Human Genre Classification for Video" as a challenge.

The majority of research in video analysis today focuses on surveillance video. While this is critical for a lot of security applications, it is incomplete in describing challenges that come up when we tackle a video retrieval and discovery application like YouTube. Analysis work beyond surveillance is often limited to specific categories like News and Sports that have well defined structures that the solution methods can explicitly work with. Our challenge aims to encourage more work in the area of semantic understanding of a broad variety of videos. Genre classification is a problem thats representative of some of the challenges that stem from the sheer diversity that can exist across video categories. The challenge will encourage new methods to solve these problems, as well as attempts at standardizing datasets to represent this problem. With internet video gaining popularity in an astounding magnitude, we believe this challenge will steer the multimedia research community towards challenges posed by the magnitude and variety of this new problem area.

We are grateful to Mor Naaman (Rutgers University) and Tat-Seng Chua (National University of Singapore) for organizing this industry challenge track at ACM Multimedia and inviting us to be a part of it.

Details of our challenge can be found here.

The bar-bet phenomenon: increasing diversity in mobile searches

Posted by Maryam Kamvar, Melanie Kellar, Rajan Patel and Ya Xu, Google Research

Historically, research suggests that web search on mobile phones has been limited when compared to the diverse set of queries which comprise computer-based search. Researchers attribute the homogeneous mobile search behavior in part to the phone's form factor and browsing capabilities. However, our new logs-based study indicates that high-end phones, like the iPhone, are changing the landscape of mobile search. We found that search from these phones has evolved not only to mimic computer web search patterns, but to exceed the expectations set by conventional web search in some cases.

We see iPhone searches mimicking computer-based search behavior in terms of query length (~3 words per query for computer and iPhone queries, as opposed to 2.5 words per query for conventional mobile queries) and query classification (notably the percentage of Adult and Entertainment searches have decreased on the iPhone relative to conventional mobile phones). But what is most surprising to us is that frequent searchers on iPhone surpass frequent searchers on computers in terms of the diversity of queries they issue. In other words, people are using high-end phones to search for a more diverse set of information needs than computers are used for; we jokingly refer to this as the "bar-bet" phenomenon -- or the "pub-quiz" phenomenon for those of you in the UK.

We devised a metric for quantifying the variability of a user’s search intentions across time. This variability metric, entro-percent, is a normalized entropy metric which compares the number of search tasks issued by a user to the number of categories those search tasks fall under. This user-variability for conventional mobile web search is much lower than for computer-based search, confirming the hypothesis that mobile web users query over a much less diverse set of topics. The surprising news is that iPhone users, on the other hand, had a higher variability than computer based users, indicating their information needs are more diverse! This shows that the challenges posed by a phone's form factor can be outweighed by its "always on, always in your pocket" benefits.

To understand the meaning of the entro-percent equation, read our full paper summarizing the findings of our logs-based study of search patterns on conventional mobile phones, iPhones and conventional computers and get all the juicy details.