Finding patterns and insights in data
Our work in this area focuses on solving key problems in database architecture and information management. Our current areas of focus are infrastructure for large-scale database systems; reducing the total cost of ownership of information management; enabling flexible ways to query, browse, and organize rich data sets containing both structured and unstructured data; and the management of database schemas and mappings.
Yanjie Fu, Yong Ge, Yu Zheng, Yao, Yanchi Liu, Hui Xiong, and Nicholas Jing Yuan, Sparse Real Estate Ranking with Online User Reviews and Offline Moving Behaviors, in ICDM 2014, IEEE – Institute of Electrical and Electronics Engineers, December 2015.
Yu Zheng, Trajectory Data Mining: An Overview, in ACM Transaction on Intelligent Systems and Technology, ACM – Association for Computing Machinery, September 2015.
Badrish Chandramouli, Jonathan Goldstein, Mike Barnett, Robert DeLine, Danyel Fisher, John C. Platt, James F. Terwilliger, and John Wernsing, Trill: A High-Performance Incremental Query Processor for Diverse Analytics, VLDB – Very Large Data Bases, August 2015.
Mohan Yang, bolin ding, surajit chaudhuri, and kaushik chakrabarti, Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers, VLDB – Very Large Data Bases, August 2015.
- ATL Cairo GPSP - Projects Ideas
- Urban Air
- Crowdsourcing and Human Computation
- Rethinking Eventual Consistency
- SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service
- Hyder, a transactional indexed-record manager for shared flash
- Tools for Software Engineers
- Academic Search
- Advanced data encryption among SQL Server 2016 top features
4 May 2015
- Build one of Microsoft's crazy Holodeck rooms at home
1 May 2015
- Microsoft's Project Oxford helps developers build more intelligent apps
1 May 2015
- Microsoft (yes, Microsoft) has a far-out vision
30 April 2015