Recent grad honored by UMN Best Dissertation Award program

Congratulations to recent graduate Ibrahim Sabek (Ph.D. 2020) for receiving an honorable mention in the University of Minnesota's Best Dissertation Award program. Winners were selected based on the originality and importance of their research, as well as the potential for the student to make an unusually significant contribution to his or her field.

His thesis, "Adopting Markov Logic Networks for Big Spatial Data and Applications" provides the first research effort to combine the two worlds of Markov Logic Networks (MLN) and spatial data analysis. The research addresses the main challenges that face any spatial analysis application when using MLN, and presents Sya, the first spatial probabilistic knowledge base construction system based on the spatial-aware MLN framework.

Sabek completed his Ph.D. in computer science in January 2020 under the supervision of Professor Mohamed F. Mokbel. During his graduate studies, he was also awarded the prestigious Doctoral Dissertation Fellowship from University of Minnesota, the first place (gold medal) of the graduate student research competition (SRC) in ACM SIGSPATIAL 2019, and the best paper nomination in ACM SIGSPATIAL 2018.

He is now working as a postdoctoral associate at the Massachusetts Institute of Technology (MIT) Computer Science & Artificial Intelligence Lab, working with Michael Cafarella (principal research scientist) and Tim Kraska (associate professor). Sabek was recently named a Computing Innovation Fellow (CIFellow) by the Computing Research Association (CRA) and the National Science Foundation (NSF). His research interests broadly include machine learning for systems, scalable data processing and querying, probabilistic databases, scalable knowledge base construction, big spatial data management and analysis, multi-query optimization and data processing in containerization environments.