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Welcome to the ADMT Lab website
Advanced Data Management Technologies Laboratory
Home of Database Group @ Pitt
 The Advanced Data Management Technologies Laboratory at the University of Pittsburgh, founded in 1996, is co-directed by Panos K. Chrysanthis and Alexandros Labrinidis. Research projects cover the entire data life cycle, from data acquisition, to data processing, exploration and analysis, to data dissemination and the approach taken is user-centric: emphasis is given on Quality of Service (QoS) and Quality of Data (QoD) returned to the users, and on controlling the trade-off between QoS and QoD, in a way that is prescribed by the users.


Recent News

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Brian T. Nixon Awarded the Orrin E. & Margaret M. Taulbee Award for Excellence in Computer Science

Congratulations to Brian T. Nixon for winning the Orrin E. & Margaret M. Taulbee Award…

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Brian T. Nixon Awarded the Orrin E. & Margaret M. Taulbee Award for Excellence in Computer Science
RETSINA presented at IPIN 2023

RETSINA presented at IPIN 2023

Kudos to Anna Baskin and Brian T. Nixon for collaborating and presenting the paper, titled…

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Recent Publications

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Current Research Projects View All

CAPRIO: Context-Aware Path Recommendation exploiting Indoor and Outdoor information
A novel graph-based data integration and routing system that leverages graph exploration algorithms and systems to unify both indoor and outdoor information.
AQSIOS: Algorithms and Metrics for New Generation Data Stream Management Systems
The goal of this project is to design a new generation of data stream management systems (DSMSs), with equal emphasis on optimizing performance and enhancing functionality.
CovidReduce
The CovidReduce group formed in April 2020 led by Prof. Panos K. Chrysanthis (Computer Science) and Prof. Walter Schneider (LRDC, Psychology, Bioengineering, Neurosurgery and Radiology) with the goal of providing ...
CAREER: User-Centric Data Management
The Web has permeated every facet of human activity. Web 2.0 is bringing a sea-change, both by the amount of user-generated content and by the level of automation for information ...