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The Third International Women’s Hackathon is now in full swing, having launched on October 11, 2014. A unique crowdsourcing event designed to empower young women leaders in computer science, the hackathon provides a fun and safe environment in which participants explore computing as a means of solving real-world problems. This year’s hackathon should draw more participants than ever, because, in response to requests from several universities, worldwide local events can participate through December 12, 2014. This means that groups who couldn’t join the virtual event on October 11 can still get in on the action.
This year, hackers are devising solutions for two worthy challenges—the Climate Data Challenge (PDF, 291 KB) and the Disaster Response Challenge (PDF, 291 KB)—sponsored, respectively, by the nonprofit organizations The Nature Conservancy and Direct Relief.
At the hackathon kickoff (which took place in Phoenix, Arizona, during the 2014 Grace Hopper Celebration of Women in Computing), participants around the world worked on these challenges, connecting virtually with one another. Those of us in Arizona were excited to link up with female hackers in India, Japan, Nepal, England, South Africa, Turkey, Pakistan, Bangladesh, Brazil, Kenya, and Trinidad & Tobago. (You can see the conversations on our Facebook page.)
I was extremely impressed by the solutions produced by our local winners in Phoenix—Team Recovery and Team Cosmos.
Other teams around the world came up with equally impressive solutions, and now, with the extended deadline, we look forward to even more innovative ideas from women hackers worldwide. We encourage you to find an event near you or start an event of your own. As an added benefit, hackathon participants can now submit their finished solutions to the Imagine Cup World Citizenship or Gaming challenges. If you have any questions, feel free to contact Microsoft Research diversity.
—Rane Johnson-Stempson, Principal Research Director, Microsoft Research
It seems that everybody today wants to employ machine learning in their research. And why not? Machine learning promises to transform our ability to understand, model, and predict the world around us. It is pushing boundaries in areas as diverse as image recognition, cardiac patient risk management, and real-time speech translation.
Despite an explosion in algorithm development, libraries, and services that has made machine learning more accessible, most researchers are not machine learning experts. It’s one thing to write a one-off model and tune it to your application—it is quite another to make that model repeatable and reliable for others to use. If only it were easier to build models and publish them straightaway, then maybe machine learning would be less impenetrable to the majority of researchers.
The recently launched Microsoft Azure Machine Learning (Azure ML) service hosted in the cloud aims to make it easier to build and deploy models for use in limitless applications. To explore this brave new world of machine learning, 50 researchers from 15 universities in France, Italy, the Netherlands, and the United Kingdom recently met at the Microsoft Research lab in Cambridge, England, eager to see how their work could be transformed.
Lab director Andrew Blake kicked off the day by highlighting some of the machine learning techniques that Cambridge lab researchers have used to develop body tracking with Kinect, TrueSkill player matching for Xbox, game and movie recommendation systems, and medical imaging methods that measure tumor growth. These achievements entailed hundreds of person years of effort, from fundamental research to applied algorithm development and implementation. Blake concluded by showing how this depth of knowledge is now available in Azure ML, for anyone to use in their own applications.
Participants then took on a hands-on journey through the web-based Azure ML Studio. Much of the work in building a predictive model involves the nitty-gritty of handling data ingress and the cleaning, slicing, and dicing of data sources of all kinds. Azure ML Studio makes this pipeline clear and easy to build, using a combination of graphical workflow and R scripts.
The real magic came at the end, when we published our best predictive model online with a mouse click—exposing it through a web application programming interface (API) instantly. This aroused great interest, as participants realized they could rapidly deploy and share models with no web API expertise.
Needless to say, we want the Azure ML platform to reach far more than 50 researchers, which is why we are offering substantial grants for researchers and data-science educators via the Microsoft Azure for Research Award program. The next deadline for grant proposals is November 15, 2014, with subsequent deadlines every two months thereafter. And, if you’re not sure but interested in testing this out, we offer a free tier of Machine Learning Studio where you can use up to 10GB of your own data. Whether you just want to get your feet wet or you are ready to dive in completely, we invite you to join the machine learning revolution. Azure ML might just transform your research.
—Kenji Takeda, Solutions Architect and Technical Manager, Microsoft Research
A year ago, the Microsoft Azure for Research project began as a small effort to help external researchers and scientists (and even Microsoft) understand how the cloud generally—and Microsoft Azure specifically—could accelerate research insights. Microsoft Azure for Research facilitates scholarly and scientific research by enabling researchers to take full advantage of the power and scalability of cloud computing for collaboration, computation, and data-intensive processing. Training events, online training, webcasts, and technical papers are just some of the resources the project provides to help researchers get up to speed with cloud computing.
The project also features an award program, which provides qualified research proposals with substantial grants of Microsoft Azure storage and compute resources for one year. The response to the award program has been overwhelming. In the past year, we have received more than 700 proposals, with submissions from all seven continents—yes, there was even one proposal from researchers in Antarctica!
I’m pleased to report that Microsoft Azure for Research has granted awards to more than half of the submitted project proposals, facilitating research in a wide range of disciplines, including computer science, biology, environmental science, genomics, and planetary science. The project clearly has tapped into the pent-up demand of researchers who want to focus their time and resources on solving complex problems rather than managing computing systems.
And while we’re still in the early days of this transition of research to the cloud, the first results are encouraging. To cite just a couple of cloud-enabled outcomes, we’ve seen urbanologists analyze big data to create new traffic-prediction models, and we’ve watched researchers from an array of disciplines work to unravel the effects of climate change on surface flooding via the National Flood Interoperability Experiment. The results of these projects and the other 360 that have received Microsoft Azure for Research grants demonstrate that Azure is a powerful resource for scholarly and scientific researchers.
If you have an idea for a cloud-enabled research project, we encourage you to apply for a Microsoft Azure for Research grant. The award program has a standing request for proposal (RFP) for any project that uses Microsoft Azure in research; these proposals are reviewed on the fifteenth of even-numbered months (February, April, June, August, October, and December). The program also issues special-opportunity RFPs, most of which have a set deadline for submission. Current special-opportunity RFPs and their deadlines include Azure Machine Learning (November 15, 2014), Climate Data (November 15, 2014), Food Resilience Climate Data (November 15, 2014), Celebration of Women in Computing (December 15, 2014), and Ebola Research (deadline is open-ended). Learn more about these RFPs.
—Dan Fay, Director, Microsoft Research