Over the past decade, Microsoft has partnered with the National Science Foundation (NSF) on three separate programs, first in 2010, and more recently through a commitment of $6M in cloud credits across two NSF supported data science programs – with the Big Data Regional Innovation Hubs and as part of the NSF BigData solicitation.

The engagement with NSF has helped Microsoft reach diverse research groups such as the Big Data Hubs¹ that brings together communities of data scientists to spark and nurture collaborations between domain experts, researchers, communities, state partners, nonprofits, and industry.

As of today, Microsoft has provided 17 cloud credit awards to Principal Investigators (PIs) who benefit from NSF supported programs. These collaborations are already seeing some interesting breakthroughs across the human body, microbial diseases, and even everyday communication –

• Franco Pestilli, Assistant Professor in Psychology, Neuroscience and Cognitive Science, Indiana University is an Azure awardee and PI through the Midwest Big Data Hub² – his group has built a platform called Brainlife using the Azure award, with the goal of fostering collaboration with sixty-six different global scientific communities such as developmental and learning sciences, network science, computer science, engineering, psychology, statistics, traumatic brain injury, vision science.
• Chirag Patel, Assistant Professor of Biomedical Informatics, Harvard Medical School is working in epigenomics, specifically by building quantitative models that demonstrate what role certain microbial species play in disease of their human host. His team used Azure credits through NSF funded Northeast Big Data Hub to analyze metagenomes en masse through a catalog of 10 million unique genes, which was computationally infeasible with on-premise laboratory resources.
• Lisa Singh, Professor, Georgetown University and an active participant with NSF’s Big Data programs and the South Big Data Hub³ is a recent recipient of an Azure award. Her group in collaboration with 3 universities and over 10 social science researchers expects to further the area of humanist and social science research given Georgetown University’s strengths in this area. One of the goals is to build a web-based platform that incorporates state of the art cloud based machine learning, natural language processing and data mining algorithms to extract meaningful big data variables (sentiment, emotion, perception, opinion, buzz, etc.) from unstructured data sources, such as newspapers, social media to empower social scientists with meaningful tools.
• Among other projects in the West region, the NSF-funded West Big Data Hub is focused on Data Science education using Jupyter notebooks running on Azure credits to rapidly scale⁴ UC Berkeley’s phenomenally successful data science education program to other institutions. As a first pilot designed to democratize data science educational access, the Foundations of Data Science course infrastructure framework was leveraged at the University of Washington this past semester.

Academia Looks to the Cloud

Academic research computing is going through a fundamental transformation evident with an increasing number of researchers and domain scientists shifting their data intensive research workloads to the cloud. With an average of more than four out of five higher education institutions already using at least one service in the cloud⁵, the widespread adoption of cloud based research computing is inevitable.

Over the past decade, Microsoft Azure has accelerated its pace of innovation to become an obvious scalable and on-demand infrastructure choice for computation dependent technology workloads.

Central IT at universities recognize the benefits and face enormous opportunities and demands to keep up with the transformation to cloud. Fortunately, pioneering funding agencies like the NSF are acknowledging the major role that public cloud providers can play in ensuring that academia is supported in their journey towards the cloud.

Microsoft is committed to a continued partnership with the National Science Foundation in its efforts to bring the power of the cloud to research computing in academia. We will continue to update the Microsoft Azure roadmap to help the community stay informed as new releases become available.

Related links

¹Microsoft Research and NSF Big Data Hubs Collaboration Passes the One-Year Mark

²Advancing Science Through a MBDH – Microsoft Research Partnership

³South Hub, Microsoft team up to provide Azure credits for researchers

⁴Passing Notebooks in Class: West Big Data Innovation Hub’s UC Berkeley and UW partner with Microsoft on shared data science infrastructure

⁵Educause Center for Analysis and Research: IT Service Delivery in Higher Education