Ibrahim Sabek is an Assistant Professor in the Thomas Lord Department of Computer Science at Viterbi School of Engineering, University of Southern California. He was a Postdoctoral Associate at the MIT Data Systems Group and an NSF/CRA Computing Innovation Fellow. He completed his PhD in computer science from University of Minnesota, Twin Cities in January 2020. His PhD work received the University-wide Best Doctoral Dissertation Honorable Mention.

Ibrahim 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.

News and Announcements
[03.2024]
   A demo paper on extracting causal conclusions from log files has been accepted in SIGMOD 2024.
[03.2024]
   I will be serving as a reviewer in the ACM Transactions on Spatial Algorithms and Systems 2024 and IEEE Transactions on Multimedia 2024.
[02.2024]

   A paper on optimizing video selection queries based on commonsense knowledge has been accepted in VLDB 2024. Source code is available here.
[02.2024]

   I had a recent interview with the Singularity Syndicate Podcast about the role of AI/ML in advancing database systems, knowledge-base extraction systems, and spatial data management and analysis [YouTube Link] [Medium Article].
[01.2024]
   I will be serving as a program committee member of SIGMOD 2025, VLDB 2025, and DBML@ICDE 2024.
[01.2024]
   I will be attending the CRA Career Mentoring Workshop in February 2024 at Washington, DC.
[12.2023]

   Our Q-Data workshop on exploiting quantum computing and quantum-inspired technologies in data-intensive systems has been accepted in SIGMOD 2024. Submission deadline is March 30, 2024. Check out our Call for Papers!
[12.2023]

   I am currently participating in the USC Viterbi's Summer High School Intensive in Next-Generation Engineering (SHINE) program as an academic host for K-12 STEM students. If you are a highly-motivated high-school student and wants to work with me, send me an email with your CV.
[11.2023]
   I have been recognized as an "Outstanding Reviewer" in SIGSPATIAL 2023 [Link].
[11.2023]

   I have been invited to give a talk on "robust and constraints-aware learning query scheduling in database systems" as a part of the "DSL Seminar" series provided by Distributed Systems Laboratory (DSL) @ University of Pennsylvania [Link].
[10.2023]
   I will be co-chairing the PhD workshop in VLDB 2024. Please consider submitting your contributions there!
[08.2023]
   I have joined the USC's Thomas Lord Department of Computer Science as an Assistant Professor.
[06.2023]
   A demo paper on optimizing video selection queries with commonsense knowledge has been accepted in VLDB 2023.
[04.2023]
   I will be serving as a reviewer in The ACM Transactions on Spatial Algorithms and Systems (TSAS) 2023.
[03.2023]
   I will be serving as a program committee member of VLDB 2024, SIGSPATIAL 2023, and GeoPrivacy@SIGSPATIAL 2023.
[03.2023]
   An MIT News article features our recent work on learning hash functions.
[03.2023]

   A recent work on "optimizing video selection queries with commonsense knowledge" has been presented in the North East Database Day 2023 (NEDB 2023).
[02.2023]

   A paper on how to exploit learned models to improve the performance of different in-memory join categories has been accepted in VLDB 2023.
[02.2023]

   I have been invited to give a talk on "building better data-intensive systems using machine learning" at the University of Minnesota's Data Management Group.
[01.2023]

   I have been invited to give a talk on "machine learning enhanced query scheduling and execution operations in database systems" as a part of the "DATA Lab Seminar" series provided by DATA Lab @ Northeastern University [Link].
[12.2022]
   I have been awarded the MIT Kaufman Teaching Certificate [Certificate Link].
[12.2022]
   I will be serving as a reviewer in The VLDB Journal 2022.
[11.2022]

   A recent Amazon Science post highlights the efforts to realize machine learning for systems research in Amazon Redshift. The post features my recent paper in SIGMOD 2022 about learned query scheduling.
[10.2022]

   A paper on studying when hashing using learned models is better than traditional and perfect hashing has been accepted in VLDB 2023. Source code is here.
[10.2022]
   I will be serving as a program committee member of SIGMOD 2024 and EDBT 2024.
[10.2022]
   I presented our work on learned query scheduling in the annual MIT DSAIL Retreat for 2022.
[04.2022]

   I have been invited as a speaker in the "work-life balance & time management" panel organized by the LASER lab at University of Massachusetts (UMASS), Amherst.
[03.2022]
   I was part of our group talk on "instance-optimized data structures and algorithms" at Facebook's Velox team.
[03.2022]

   I have been invited to give a talk on "learning query scheduling for analytic database systems" as a part of the "Cornell Database Seminar" series provided by Cornell Database Group [Link].
[03.2022]
   A paper on learning query scheduling for analytic workloads has been accepted in SIGMOD 2022.
[03.2022]

   I will be serving as a program committee member of SIGMOD 2023, VLDB 2023, ICDE 2023, SIGSPATIAL 2022, and AutoML-Conf 2022.
[07.2021]
   A paper on using learned models for hashing has been accepted in the AIDB workshop @ VLDB 2021.
[05.2021]

   I am honored to receive the University-wide Best Dissertation Honorable Mention for my PhD thesis "Adopting Markov Logic Networks for Big Spatial Data and Applications" [Link].
[05.2021]

   A medium post on our recent work that proposes using distance-bounded spatial approximations to exploit modern hardware and accelerate spatial queries.
[04.2021]

   I will be serving as a program committee member of SIGMOD 2022, EDBT 2022, SIGSPATIAL 2021, GEOProcessing 2021, AutoML@ICML 2021 and SpatialAPI@SIGSPATIAL 2021.
[04.2021]

   A post by the Computing Community Consortium (CCC) highlights my current research on "Machine Learning for Storage and Execution Layers of Database Systems" [Link].
[04.2021]
   An advanced seminar on the recent advances of machine learning for big spatial data has been accepted in MDM 2021.
[03.2021]

   I have been invited to give a talk on "The Landscape of Machine Learning for Big Spatial Data" as a part of the "Spatial Data Handling" series provided by University of Maryland Institute for Advanced Computer Studies (UMIACS) [Link].
[03.2021]

   Selected as the sole CSE departmental nominee for the University-wide Best PhD Dissertation Competition 2021 of University of Minnesota, Twin Cities.
[10.2020]
   A paper on approximate spatial data processing has been accepted in CIDR 2021.
[09.2020]


   I am honored to be named Computing Innovation Fellow (CIFellow) by the Computing Research Association (CRA) and the National Science Foundation (NSF). I have been selected among the top 10% of researchers from over 140 universities that span a wide variety of computing research areas [Link].
[07.2020]
   A paper on using machine learning to build efficient spatial indexes has been accepted in the AIDB workshop @ VLDB 2020.
[05.2020]
   I will be serving as a program committee member in ACM SIGSPATIAL 2020 and its co-located SpatialAPI workshop.
[04.2020]
   I will be serving as a program committee member in the AutoML workshop @ ICML 2020.
[02.2020]

   I have joined MIT CSAIL as a postdoctoral associate. I will be a part of the Data Systems and AI Lab (DSAIL) and work closely with Prof. Tim Kraska.
[01.2020]
   I have successfully defended my PhD in computer science from University of Minnesota, Twin Cities.
[12.2019]
   Our tutorial on the intersection between machine learning and big spatial data has been accepted in IEEE ICDE 2020.
[11.2019]

   An extension paper on our Flash system for scaling up the performance of spatial probabilistic graphical modeling has been published in SIGSPATIAL Special.
[11.2019]

   I have won the first place (gold medal) of the graduate Student Research Competition (SRC) in ACM SIGSPATIAL 2019. Now, I am advanced to the ACM-Wide SRC grand finals [Link].
[10.2019]

   A full paper on exploiting Markov Logic Networks (MLN) to scale up the performance of multinomial autologistic regression models has been accepted in ACM TSAS.
[10.2019]

   A full paper on enabling spatial awareness inside probabilistic knowledge base construction systems has been accepted in IEEE ICDE 2020.
[09.2019]
   I am invited to give a talk about "Adopting Markov Logic Networks for Big Spatial Data and Applications" at MIT.
[09.2019]

   An extended abstract on scaling up the performance of spatial probabilistic graphical models using Markov Logic Networks (MLN) has been accepted in the student research competition of ACM SIGSPATIAL 2019.
[07.2019]

   We are pleased to receive the National Science Foundation (NSF) IIS Award ($500,000) based on the core of my PhD work. In this grant, I was a major contributor in the project design, development, and writing.
[07.2019]

   We have been invited to give a tutorial on the recent advances in the intersection between machine learning and big spatial data in SSTD 2019. The tutorial will be given by Prof. Mokbel on 08/20.
[07.2019]
   I will be serving as a technical program committee member in GEOProcessing 2020.
[06.2019]
   I have received the "NSF Travel Grant Award" for attending VLDB 2019.
[05.2019]

   A paper highlighting my research directions in adopting Markov Logic Networks (MLN) for big spatial data and applications has been accepted in the PhD workshop @ VLDB 2019.
[05.2019]

   A demo paper on scaling up the performance of spatial probabilistic graphical models using Markov Logic Networks (MLN) has been accepted in VLDB 2019.
[04.2019]

   I am honored to receive the prestigious "Doctoral Dissertation Fellowship Award" for academic year 2019 - 2020 from University of Minnesota, Twin Cities [Link].
[04.2019]
   A tutorial on the synergy between machine learning and big spatial data has been accepted in VLDB 2019.
[02.2019]

   A short paper on building a framework for data-intensive applications in containerized environments has been accepted in IEEE ICDE 2019.
[01.2019]

   My CRA project in Microsoft Research Redmond has been used to build both offline and streaming analytics platforms such as Quill and online microservice fabrics such as Ambrosia.
[12.2018]
   I have passed my PhD thesis proposal exam.
[10.2018]
   I have received the "NSF Travel Grant Award" for attending ACM SIGSPATIAL 2018.
[09.2018]

   Our TurboReg paper has been selected among top 6 best papers in ACM SIGSPATAL 2018, and has been invited for a special issue of ACM TSAS on best papers [Link].
[08.2018]

   A full paper on scaling up the performance of binary spatial autologistic regression models has been accepted in ACM SIGSPATIAL 2018.
[02.2018]
   A demo paper on spatial probabilistic knowledge base construction has been accepted in ACM SIGMOD 2018.
[10.2017]
   I will be representing our Data Management Lab at the 2017 Research Showcase Exhibit of University of Minnesota.
[10.2017]
   I have received the "NSF Travel Grant Award" for attending ACM SIGSPATIAL 2017.
[09.2017]

   The CRA project, that I have started while doing my second internship in Microsoft Research Redmond, has been released as open source on github.
[08.2017]

   A full paper on optimizing the performance of spatial join operations in MapReduce frameworks has been accepted in ACM SIGSPATIAL 2017.
[05.2017]
   I have been selected among the top 10 finalists in the student research competition of ACM SIGMOD 2017.
[05.2017]
   A full paper on supporting spatial data processing inside Impala framework has been accepted in SSTD 2017.
[03.2017]
   I will be going back to the database group at Microsoft Research Redmond to spend Summer 2017 as a research intern.
[02.2017]
   I have received the "ACM Student Travel Award" for attending ACM SIGMOD 2017.
[01.2017]

   An extended abstract on optimizing spatial queries in MapReduce frameworks has been accepted in the student research competition of ACM SIGMOD 2017.
[04.2016]
   I have completed my M.Sc. degree in computer science from University of Minnesota, Twin Cities.
[02.2016]
   I will be spending Summer 2016 as a research intern in the database group at Microsoft Research Redmond.
[01.2016]

   I am honored to receive the "Academic Excellence Fellowship Award" for Spring 2016 from University of Minnesota, Twin Cities.
[10.2015]
   I have received the "NSF Travel Grant Award" for attending ACM SIGSPATIAL 2015.
[04.2015]
   I will be spending Summer 2015 as a research intern at NEC Labs America.
[01.2015]
   I am honored to receive the "Graduate School Fellowship Award" for Spring 2015 from University of Minnesota, Twin Cities.