Ibrahim Sabek

Ibrahim Sabek is an Assistant Porfessor 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 recieved the University-wide Best Doctoral Dissertation Honorable Mention.

Ibrahim is interested in building the next generation of machine learning-empowered data management, processing and analysis systems. His research focuses on deeply understanding both machine learning and systems techniques, resulting in entirely new designs, algorithms, and data structures for data-intensive systems and applications.

I am actively looking for PhD, MSc, and undergraduate students to work with me. If you are interested, email me your CV along with a short description of any research experience you have, if any.

News and Announcements


[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, and 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.