The Qatar Computing Research Institute (QCRI) - MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) research collaboration is a medium for knowledge joint-creation, transfer, and exchange of expertise between QCRI and MIT CSAIL scientists. Scientists from both organizations are undertaking a variety of core computer science research projects -- database management, Arabic language technology, new paradigms for social computing, and data visualization, etc., with the goal of developing innovative solutions that can have a broad and meaningful impact. The agreement also offers CSAIL researchers and students exposure to the unique challenges in the Gulf region. Scientists at QCRI are benefiting from the expertise of MIT’s eminent faculty and researchers through joint research projects that will enable QCRI to realize its vision to become a premier center of computing research regionally and internationally.
This project aims to develop accurate map-making techniques using crowd-sourced methods to overcome challenges related to creating and maintaining street maps, especially in a rapidly developing en
The major goal of the project is to understand the food habits from social media images.
This project aims to develop a complete system for delivering high-quality stereoscopic broadcast video. We focus on the real-time video of sporting events and soccer in particular.
We aim to assess the current tactics used by Qataris and other GCC nationals to express identity through uses of virtual identity technologies (e.g., social media profiles and avatars), which are n
This project began as a data integration project to explore interactive data curation. It has since expanded to various aspects of data management, including elasticity in transactional DBMSs.
This project aims to develop speech and language processing technologies that will support natural interaction via spoken language. Specific research objectives include developing technologies tha
Current shared computing platforms, from small clusters to large datacenters, suffer from low utilization, wasting billions of dollars in energy and infrastructure every year.
Information technologies today can inform each of us about the best alternatives for shortest paths from origins to destinations, but they do not contain incentives or alternatives that manage the
This project falls into three categories: 1) the use of machine learning and other advanced analytical techniques to discover new information related to on-field performance, and 2) the developme
This project focuses on how data management can be used to facilitate social computing.
The research challenge we address is that of securing computing infrastructure against a broad class of cyberattacks.
We propose a new study type to understand the basis of complex genetic traits, a functional genome-wide association study (fGWAS). Most current experimental designs, relying solely on linear model
Research Objectives and Milestones Summary
Problem: How is memory implemented in the human brain?
The goal of the project is to design a high-throughput and low-power FPGA implementation of the newly proposed sparse FFT algorithm. For the purposes of guiding the implementation
MAQSA is a system for social analytics on news. MAQSA provides an interactive topic-centric dashboard that summarizes news articles and social activity (e.g., comments and tweets) around them.
This research seeks to develop motion magnification and comparison techniques for sports applications, and to develop motion magnification techniques for laparoscopic surgery.
Our objective is to answer the question: How can users get the full benefits of multi-user software even when their friends and colleagues use different software vendors, platforms, and service pro