Cloud computing is changing the model of cyber infrastructure for Academic Research. Microsoft is supporting the efforts of the Pervasive Technology Institute (PTI) at Indiana University to go beyond technology to invest in the people on campus who work with the Academic Research community to adopt technologies and tools that enhance collaboration, accelerate discovery, and share findings.
This Humanware project will provide an honorarium payment, cloud credits, and technical support to individuals on college campuses that apply directly to PTI to become members of the Cloud Research Software Engineers (CRSE) community. This is community that prides itself on combining technical expertise with human skills to help others across campus.
PTI Program Management and First Wave CRSEs attending Campus Computing Summit 2019
Brian Voss | Research Engagement Manager
Brian Voss, who originated the Humanware term, is leading this initiative for Indiana University as the Research Engagement Manager responsible for building the CRSE community at campuses throughout the US and North America. Brian is a respected technology executive with over 25 years experience with Higher Education institutions as CIO, and director of research computing infrastructure.
Craig Stewart, Executive Director of the Pervasive Technology Institute and recipient of the grant, will be participating in CCS and discussing industry collaboration to benefit the Academic Research community.
Eight applicants have been accepted as First Wave members of the CRSE Community from Rice, UNC, Perdue, UC -Berkeley, U. Nebraska – Lincoln, Georgia Tech, Stanford, and U. Kentucky.
The following CRSEs will kick off the program, visiting Microsoft Headquarters in Redmond, WA and participating as guests in Campus Connections Summit 2019.
John Mulligan | Rice University
John will work with Humanities and Social Science focused teams to design and deliver interactive visualizations that allow researchers to see their data in a new light, and build custom web interfaces to automate the cross-indexing of several databases, allowing his researchers to accelerate and share their work.
Eleftheria (Ria) Kontou | University of North Carolina
Ria proposes to use Microsoft Azure Machine Learning Studio to integrate geospatial data from GPS, travel surveys and trip datasets with socio-demographics and economic characteristics, to assess the impacts of ride-sourcing on transportation’s systems safety. It will use 1.5 million ride-sourcing trips data from Austin TX, overlaid with accident and traffic datasets. The proposal will seek to leverage Applicant uses econometric models (time-series with spatial autocorrelation) and heuristic algorithms to perform the analysis.
Kris Ezra | Purdue University
Kris is proposing to enhance and exercise a model with respect to metrics of interest within a stochastic, parametrically defined design space, to showcase the tremendous benefit of high-performance cloud computing environments as efficient, cost effective, and well-suited to Systems of Systems (SoS) research, now and in the future.
Dan Sholler | University of California – Berkeley
Dan will study the status of cloud research in a discipline to categorize the types of research employing cloud-based tools, and document how cloud computing has changed the methodological approaches, research roles, and necessary skills required for scientific discovery. The proposal aims to develop actionable recommendations for promoting cloud research, governing cloud services use, and augmenting the humanware systems scientists rely upon to coordinate discovery.
Derek Weitzel | University of Nebraska – Lincoln
Derek will work with UNL community to advance the integration of cloud CI resources by adopting an NSF project, SciTokens, to securely store and transfer identity tokens, which allow access to secure storage and computing resources. This aims to overcome a barrier in using commercial cloud CI services: the management of security credentials.
Nuyun (Nellie) Zhang | Georgia Institute of Technology
Nellie, in her role with GaTech PACE will provide training and one-on-one support of the GA Tech research community, integrating Microsoft Azure HPC into their existing workflows for machine learning and data intensive research.
The CRSEs below are starting at the same time but are unable to visit Redmond this week due to scheduling conflicts.
Josiah K. Leong | Stanford University
Josiah will work with his lab to use Micrpsoft Azure’s Cognitive Services platform to analyze neuroimaging data from the Adolescent Brain Cognitive Development study.
Yongwook Song | University of Kentucky
Yongwook will work with his team to develop a machine learning-based data analysis platform using Microsoft’s Azure TensorFlow estimator API and TFRecordDataset to maximize throughput and the utilization of cloud-scaled GPUs against single molecule studies of in vivo protein oligomerization.