Spatial Sciences Institute

Ibrahim Sabek

Assistant Professor of Computer Science and Spatial Sciences

Email sabek@usc.edu Office Ginsburg Hall GCS 505C Office Phone 213.821.2292

Profile

Ibrahim Sabek is an assistant professor in the Thomas Lord Department of Computer Science and in the Spatial Sciences Institute at University of Southern California. Before joining USC, he was a postdoctoral associate at the MIT CSAIL Data Systems Group and an NSF/CRA Computing Innovation Fellow from 2020 to 2023.

Dr. Sabek is interested in building the next generation of data management, processing and analysis systems using machine learning and quantum computing. His research focuses on deeply understanding fundamental techniques in machine learning, quantum computing, and systems design, resulting in entirely new designs, algorithms, and data structures for data-intensive systems and applications. He also broadly researches data management for machine learning systems, scalable knowledge base construction, big spatial data management and analysis, video analytics, and causal analysis.

Education

Ph.D., Computer Science, University of Minnesota; recipient, University-wide Best Doctoral Dissertation Honorable Mention Award

M.S., Computer Science, University of Minnesota

M.S., Computer and Systems Engineering, Alexandria University

B.S., Computer and Systems Engineering, Alexandria University

Recent Publications

“Optimizing Video Selection LIMIT Queries With Commonsense Knowledge”, Wenjia He, Ibrahim Sabek, Yuze Lou, and Michael Cafarella
International Conference on Very Large Data Bases (VLDB), 2024

“The Case for Learned In‑memory Joins”, Ibrahim Sabek and Tim Kraska International Conference on Very Large Data Bases (VLDB), 2023

“Can Learned Models Replace Hash Functions?”, Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, and Tim Kraska
International Conference on Very Large Data Bases (VLDB), 2023

“LSched: A Workload‑Aware Learned Query Scheduler for Analytical Database Systems”, Ibrahim Sabek, Tenzin Samten Ukyab, and Tim Kraska
ACM International Conference on Management of Data (SIGMOD), 2022

“The Case for Distance‑Bounded Spatial Approximations”, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Varun Pandey, Harish Doraiswamy, and Volker Markl, Conference on Innovative Data Systems Research (CIDR), 2021