Microsoft Research announces winners of the Open Source Challenge

By Judith Bishop

Topic
Big Data
Cloud

In February, Microsoft Research announced an Open Source Challenge for students who want to solve interesting science or societal problems using open source technologies. Applicants utilized one of the more than fifty Microsoft Research open source projects that span the range of computer science, from artificial intelligence and visualization to cryptography and programming models.
Interest over the past three months came from all around the world and the impressive results are in…
Akond Rahman, a second-year student in the computer science doctoral program at North Carolina State University, won the Grand Prize. In his winning submission, Akond makes use of the Send2Vec, which are the predictors and trained model files of DSSM (deep structured semantic model or deep semantic similarity model) to quantify the semantic similarity of software projects.
“Small teams of engineers working in large corporations [and institutions] are constantly having to start from scratch—they can’t get anything useful out of the software repositories,” said Rahman. “If I could use a deep learning neural network like DSSM to do the semantic search and arrange and score the tokens, teams would be able find and reuse code that other teams had already created.”
In addition to the grand prize, Microsoft Research announced the winners of three second prizes:

Varun Agrawal (Georgia Tech), for “OneGroup—Automated Photo Sharing via Facial Recognition,” which uses Microsoft Cognitive Services (formerly Project Oxford) to create an automated photo-sharing feature that integrates Microsoft OneDrive and the Outlook Contacts API. It optimizes sharing flows for customers by answering the question “how do I share more easily?”
Saeid Tizpaz Niari (University of Colorado-Boulder), for “CONfidentiality CERTifier, a Modeling and Verification Framework for Program Confidentiality,” which extracts a nondeterministic transducer abstraction from programs and uses transducer techniques for analysis. A prototype tool was built around the Z3 theorem prover.
Yida Wang (Beijing University of Posts and Telecommunications) for “CNTK on Mac: 2D Object Restoration and Recognition Based on 3D Model,” which synthesizes and renders 2D images with and without background, and uses the Computational Network Toolkit (CNTK) to train a segmentation and restoration model to restore the foreground image. CNTK’s open source was changed to support CNTK on Mac for object recognition based on 3D object or normal photos.

“The Open Source Challenge did exactly what we’d hoped: the winning students — some of whom hadn’t known about the offerings available through the Open Source for Academics program at Microsoft—found the tools they needed to solve real problems,” wrote Judith Bishop, Director of Computer Science, Microsoft Research. “Their takeaway from the experience—in addition to the prizes and, we hope, the greatly-deserved awe of their colleagues—is that they have a new source for tools to help them with future projects, solving future problems.”
For more on the winners and the Open Source for Academics resources, check out the Microsoft Research blog. Congratulations to the winners!