Alexandros Labrinidis

  • Professor

Dr. Alexandros Labrinidis received his Ph.D degree in Computer Science from the University of Maryland, College Park in 2002. He is currently a professor at the Department of Computer Science of the University of Pittsburgh and co-director of the Advanced Data Management Technologies Laboratory (ADMT Lab). He is also an adjunct professor at Carnegie Mellon University (CS Dept).

Dr. Labrinidis' research focuses on user-centric data management for scalable network-centric applications, including web-databases, data stream management systems, sensor networks, and scientific data management (with an emphasis on big data). He has published over 70 papers at peer-reviewed journals, conferences, and workshops; he is the recipient of an NSF CAREER award in 2008. Dr. Labrinidis served as the Secretary/Treasurer for ACM SIGMOD and as the Editor of SIGMOD Record. He is currently on the editorial board of the Very Large Databases Journal and of the Parallel and Distributed Databases Journal. He has also served on numerous program committees of international conferences/workshops; in 2014, he was the PC Track-Chair for Streams and Sensor Networks for the ICDE conference.

Representative Publications

A. Zheng, A. Labrinidis, P. Pisciuneri, P. Chrysanthis, and P. Givi, "PARAGON: Parallel Architecture-Aware Graph Partition Refinement Algorithm," 19th International Conference on Extending Database Technology, Bordeaux, France, March, 2016.

A. Shein, P. Chrysanthis, and A. Labrinidis, "Processing of Aggregate Continuous Queries in a Distributed Environment ," BIRTE 2015 and VLDB 2015, Kohala Coast, HI, 2015.

T. Pham, P. Chrysanthis, and A. Labrinidis, "Avoiding Class Warfare: Managing Continuous Queries with Differentiated Classes of Service ," VLDB Journal, 2015.

A. Zheng, A. Labrinidis, and P. Chrysanthis, " Planar: Parallel Lightweight Architecture-Aware Adaptive Graph Repartitioning," 32nd IEEE International Conference on Data Engineering (ICDE 2016), Helsinki, Finland, May 2016.

Research Interests

Big data
User-centric data management
Scientific data management
Data stream management systems
Data-intensive computing
Collaborative systems
Quality of data/quality of service
The deep Web