AWS in Education will evaluate academic research support proposals from active faculty at accredited universities and colleges throughout the year. We will review and award select recipients 4 times a year. Criteria include but are not limited to the uniqueness of the work, application of Amazon Web Services, and the ability to disseminate the work publicly via papers, events, or public relations. Grant amounts will vary depending on the research proposal and usage requirements documented in the proposal. Grants will be in the form of credits applicable to AWS services. EC2 usage within the grants will be for on-demand instances only.

Recent Recipients

MIT, Mark Pearrow, McGovern Institute
Genetic and computational analysis, electrophysiological recordings, and non-invasive brain imaging

University of California Berkeley, Dan Werthimer, Center for Astronomy Signal Processing and Electronics Research
Identification and analysis of transient astronomical radio phenomena

University of Illinois Urbana-Champaign, Indranil Gupta, Computer Science
Research issues in loosely federated clouds

Singapore Management University, Ming Jiang
New techniques in malware analysis

Technion, Israel Institute of Technology, Alex Zlotnik
Systems for efficient execution of scientific workloads

University of Surrey, Lee Gillam, Department of Computing
Use cases for cloud computing in research supporting UK academic computing network

Florida International University, Seyed Masoud Sadjadi, Department of Computer Science
Provisioning systems for virtual laboratories supporting curriculum

University of Maryland, Michael Schatz, Center for Bioinformatics and Computational Biology
Assembly of large genomes using cloud computing

ETH Zurich, Till Quack, Computer Vision Lab
Large scale annotation of photo collections

University of Pennsylvania, Zachary Ives, Computer and Information Science Department
Orchestra, collaborative data sharing system on the cloud

Monash University, Blair Bethwaite, eScience and Grid Engineering Laboratory
Mixing grids and clouds for high throughput science

Johns Hopkins, Benjamin Langmead, Bloomberg School of Public Health
Highly scalable measurement of differential expression with next-generation sequencing and cloud computing

Universitat Pompeu Fabra, Andy Pohl, Centre de Regulacio Genomica
Steroid-hormonal regulation of genes in breast cancer

Indiana University, Geoffrey Fox, Pervasive Technology Institute
Proof of concepts linking FutureGrid users to AWS

Newcastle University, Hamish Harvey, Flood Risk Management Research Consortium
Decision analysis for managing flood risk in coastal cities

University College London, Robert Rentzsch, Biochemistry
Genome modeling and model annotation

Northeastern University, Alan Mislove, College of Computer and Information Science
Tracing the spread of information in social networks

Harvard University, Vinothan N. Manoharan, SEAS, Department of Physics
Exploring the physics of self-organization with digital holographic microscopy

University College Dublin, Thomas Brady, Heterogeneous Computing Laboratory
SmartGridSolve—converting applications to high performance applications on AWS

University of Michigan, Christopher Maher, Center for Translational Pathology
Gene fusion discovery in cancer transcriptomes

The American University in Cairo, Ahmed Fathalla, Computer Science and Engineering
Location based search engine

University of Washington, Michael Hochberg, Nanophotonics Lab
Adapting integrated photonic technology in silicon for a variety of new applications

University of California San Francisco, Taylor Sittler, Viral Diagnostics and Discovery Center
Deep sequencing for influenza virus detection and discovery

Columbia University, Haimonti Dutta, The Center for Computational Learning Systems
A distributed framework for learning on EEG data obtained from epilepsy patients

Stanford University, Monica Lam, Department of Computer Science
Applications for decentralized social networking infrastructure

Carnegie Mellon University, Tudor Dumitras, Electrical and Computer Engineering
Imago, an approach for removing leading causes of software upgrade failures via upgrades-as-a-service

University of Wales Bangor, Anna Croft, School of Chemistry
Understanding cell wall components of Mycobacterium Tuberculosis

University of Heidelberg, Sergey Koposov, Max Planck Institute for Astronomy
Analyzing stellarstreams on AWS to complete Milky Way picture

Duke University, Landon Cox, Computer Science Department
Vis-a-Vis, a service enabling personal virtual machines for managing personal information online

University of Washington, Christopher Murray, Global Burden Disease Study
Systematic assessment of the data on all diseases and injuries, and produce comprehensive and comparable estimates of the burden of diseases, injuries and risk factors for two time periods

MIT, Samuel Madden, Computer Science and Artificial Intelligence Laboratory
Load aware scaling for distributed databases

National University of Singapore, Jiang Dawei, Computer Science
MapReduceDB: A unified data processing system

University of Virginia, Jason Lawrence, Department of Computer Science
Image super-resolution using trillions of examples

Tulsa Community College, Thomas Mancino, Wavebreak.org
Developing cloud-based education tool with cloud curriculum

University of California San Francisco, David Quigley, Diller Comprehensive Family Cancer Center
Analysis to identify genes that function in normal lung biology as well as in lung tumor pathology

University of Stuttgart, Ralph Mietzner, Institute of Architecture and Application Systems
Automated deployment and management of composite applications distributed across cloud computing environments.

SUNY Stony Brook, Steven Skiena, Department of Computer Science
Lydia/TextMap news analysis project at Stony Brook University combines natural language processing (NLP), distributed processing and statistical analysis to reduce news steams to time series on the frequency and sentiment of each person, place, or thing.

Stanford University, Jacob Leverich, Department of Computer Science
Energy efficiency of clusters and data centers that make extensive use of MapReduce

University of California Lawrence Berkeley National Lab, Greg Aldering, The Nearby Supernova Factory
Understanding the origin of supernovae, how they explode, and how to better calibrate them as distance indicators

SUNY Binghamton, Kenneth Chiu, with U. Wisconsin-Madison, U. Western Australia, National Center for High-Performance Computing, Taiwan
Ecosystem modeling analysis from grids to cloud services and AWS.

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