“Distributed and Adaptive Personalized Medicine”
08/17 – 07/19 Award #1723483 (Shin)
National Science Foundation (Smart and Connected Health)
The use of clinical data is at the core of medical practice today and, while various mathematical and computational approaches have been developed, conventional approaches are not geared towards individual patients or the dynamics of constantly changing clinical data. Inspired by studies of multi-cellular dynamics, this project explores distributed and adaptive personalized medicine which collectively learns from an individual’s clinical data in real time through localized interactions. To make these efforts possible and scalable, this project will exploit a microservice (actor model)-enabled cloud cyberinfrastructure for increased accessibility, adaptability, interoperability, extensibility, scalability and sustainability. In addition, the result of this project, including the mathematical framework, can be applied to other domains, such as education, energy, telecommunications, and transportation. It will also be disseminated to academia through publications, seminars, workshops, and a MOOC to integrate the results of this work into interdisciplinary biomedical informatics research. All tools and documentation will be made available on GitHub so that a sustainable community can be formed around the project.
Total costs: $288,056
“A Cloud-enabled HPC Infrastructure for Materials Genomics, Big Data and Big Compute Sciences”
06/15 – 05/18 Academic Plan (Multi-PI: Rajasekaran, Ramprasad, Shin)
University of Connecticut
The major goal of this project is to build a high-performance on-campus cloud infrastructure aimed at Big Data and Big Compute Science, including materials genomics, computational systems biology, and biologically-inspired cloud computing.
Total costs: $1,400,000 (equipment grant)
“Cloud-enabled Smart Microscopes for Biomedical Imaging”
06/15 – 05/16 MS-AZR-0036P (Shin)
Microsoft Azure Research Award
Biological imaging enabled by advances in microscopy and software (e.g., image processing) has played an important role in biological research. µManager is an open-source, cross-platform desktop application, to control a wide variety of motorized microscopes, cameras, stages, illuminators, and other microscope accessories. This project will develop a cloud-enabled smart microscope solution that integrates µManager applications to achieve automated and advanced image acquisition, processing, and analysis.
Total costs: $20,000 (cloud resource credit)
“Engineering as a Service (EaaS) for Complex Intelligent Systems”
09/14 – 08/15 MS-AZR-0036P (Shin)
Microsoft Azure Research Award
This project will develop a community-driven open source Service-Oriented Architecture (SOA) that provides computational engineering components/tools as web services, “Engineering as a Service (EaaS)”, for the study of complex intelligent systems. This proof-of-concept EaaS will enable engineers, scientists, and students to develop customized complex web applications/services using interoperable, reusable building blocks. Furthermore, EaaS will be integrated with popular engineering software development environments such MATLAB or LabVIEW. This integration will eventually lead to the Internet of Things (IoT) or cloud-enabled cyber-physical systems.
Total costs: $50,000 (cloud resource credit)