Ph.D. Student Ibrahim Sabek Wins ACM SIGSPATIAL Student Research Competition
Ph.D. student Ibrahim Sabek placed first in the ACM SIGSPATIAL Graduate Student Research Competition for his paper “Towards Scalable Spatial Probabilistic Graphical Modeling.”
The current explosion in spatial data raises the need for efficient spatial analysis tools to extract useful information from such data. However, existing tools are neither generic nor scalable when dealing with big spatial data. This work presents Flash; a framework for generic and scalable spatial data analysis, with a special focus on spatial probabilistic graphical modelling. Flash exploits Markov Logic Networks (MLN) to efficiently express the different spatial probabilistic graphical models as a set of declarative logical rules. In addition, Flash provides spatial variations of the scalable learning and inference techniques of MLN to efficiently perform the learning and prediction operations in these spatial models
Sabek's interests include scalable data processing and querying, probabilistic databases, scalable spatial analysis and computing, statistical learning and inference, big spatial data management, and scalable knowledge base construction. He works with Professor Mohamed Mokbel as part of the Data Management Lab.
As the winner of SIGSPATIAL Graduate Student Research Competition, Sabek will represent ACM SIGSPATIAL in the SRC Grand Finals, where winners from ACM SIGs are evaluated to nominate the ACM-wide SRC winners.
This is the second year that a student from Professor Mokbel's lab has won this award. Ph.D. student Louai Alarabi was recognized at the 2018 conference.
Please join the Department of Computer Science and Engineering in congratulating Ibrahim Sabek on this achievement and wish him luck at the Grand Finals!