Dr. Essam Mansour

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Scientist
Cyber Security
I am proud to contribute to the growing effort of establishing QCRI as a world-class research institute in applied computing by developing theories and systems of high impact for both academia and industry.

Research Focus at QCRI

Dr. Essam Mansour works as a Scientist at Qatar Computing Research Institute (QCRI). He joined QCRI in June, 2013. Dr. Essam Mansour received his Ph.D. in Computer Science in 2008 from Dublin Institute of Technology (DIT), Ireland. He graduated from Cairo University, Egypt in 2000 with a First Class Honours B.Sc. in Information Systems, and in 2003 with an M.Sc. in Information Systems. He was a Research and Teaching Fellow in International University in Germany Bruchsal from July 2008 to Oct 2009, and in King Abdullah University of Science and Technology (KAUST) from Oct 2009 to Jun 2013.

Dr. Mansour's research interests are in the broad areas of parallel/distributed systems, data management, and machine learning for developing scalable systems for big data. His current research focuses on the following areas:

  • Discovery and analytics on large datasets
  • Parallel query processing on large graphs and strings
  • Distributed and federated RDF engines for linked data
  • A unified infrastructure for cyber security applications.

Previous Experience

Before joining QCRI, Dr. Mansour was a research fellow at King Abdullah University of Science and Technology (KAUST) where he led a project for developing a framework for a cloud-based string database system. The project aimed to bridge the gap between Big Data analytics and cloud computing.

Dr. Mansour has developed different parallel string operators, such as maximal pairs and motif extraction. His system utilizes multi-core systems, clusters and supercomputers. Compared to recent methods, his system can expect much faster execution while supporting 2-3 orders of magnitude more data than existing methods. Moreover, his system reports scalability up to 16,384 cores on a supercomputer.

Dr. Mansour delivered a complete course in Cloud Computing at KAUST. Additionally, he offered different lectures on advanced data management for KAUST students.

Professional Experience

  • King Abdullah University of Science and Technology (KAUST), Research Fellow Oct, 2009 – Jun, 2013
  • International University in Germany, Research Associate, Jul 2008 -  Oct 2009

Professional Associations and Awards

  • Reviewer of IEEE Transactions on Knowledge and Data Engineering (TKDE), Cloud Computing (TCCSI), and Big Data (TBD)
  • PC member of SIGMOD 2016, ICDE 2016, DASFAA15, ICDCS 2015, CCGrid2014, and iiWAS 2014
  • Distinguished Reviewer Award from Very Large Data Bases (VLDB) 2018

Education

  • PhD, Dublin Institute of Technology (DIT), Ireland, 2008
  • MSc, Cairo University,  Egypt, 2003
  • BSc, Cairo University,  Egypt, 2000

Selected Research

  • Majed Sahli, Essam Mansour, Panos Kalnis: StarDB: A Large-Scale DBMS for Strings. The Proceedings of the VLDB Endowment (PVLDB) 8(12), 2015
  • Majed Sahli, Essam Mansour, Tariq Alturkestani, Panos Kalnis: Automatic tuning of bag-of-tasks applications. International Conference on Data Engineering (ICDE), 2015
  • Rebecca Taft, Essam Mansour, Marco Serafini, Jennie Duggan, Aaron J. Elmore, Ashraf Aboulnaga, Andrew Pavlo, Michael Stonebraker: E-Store: Fine-Grained Elastic Partitioning for Distributed Transaction Processing. The Proceedings of the VLDB Endowment (PVLDB) 8(3), 2014
  • Marco Serafini, Essam Mansour, Ashraf Aboulnaga, Kenneth Salem, Taha Rafiq, Umar Farooq Minhas: Accordion: Elastic Scalability for Database Systems Supporting Distributed Transactions. The Proceedings of the VLDB Endowment (PVLDB) 7(12), 2014
  • Majed Sahli, Essam Mansour, Panos Kalnis: ACME: A scalable parallel system for extracting frequent patterns from a very long sequence. VLDB Journal 23(6), 2014
  • Majed Sahli, Essam Mansour and Panos Kalnis. "Parallel Motif Extraction from Very Long Sequences". In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, California, USA.
  • Essam Mansour, Ahmed El-Roby, Aron Ahmadia, Panos Kalnis, Ashraf Aboulnaga. Cloud Repeat Analytics for Very Long Sequences. The Proceedings of the VLDB Endowment (PVLDB), 2013.
  • Essam Mansour, Amin Allam, Spiros Skiadopoulos, and Panos Kalnis. ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings. In the volume 5 of Proceedings of the VLDB Endowment (PVLDB), 2011.
  • Essam Mansour and Hagen Höpfner. An Approach to Detecting Relevant Updates to Cached Data Using XML and Active Databases. In Proceedings of the 12th International Conference on Extending Database Technology (EDBT), 2009.
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In the Media

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Can AI Put An End To Fake News? Don't Be So Sure

07/10/2018

Fake news was the Collin’s word of the year for 2017 with good reason. In a year where politics-as-usual was torn apart at the seams, high-profile scandals rocked our faith in humanity and the ...

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MIT/QCRI system uses machine learning to build road maps

22/04/2018

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...

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Improving disaster response efforts through data

08/02/2018

Extreme weather events put the most vulnerable communities at high risk. How can data analytics strengthen early warning systems and and support relief efforts for communities in need? The size and ...

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Upcoming Events

2019

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“The Future of Higher Education in the Age of Technological Disruption” by CMU President Dr. Farnam Jahanian

Download ICS File 24/03/2019 ,

Dr. Farnam Jahanian, the President of Carnegie Mellon University, will deliver a public lecture, “The Future of Higher Education in the Age of Technological Disruption” at CMU’s Qatar campus on Sunday, March 24.

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QCRI - MIT CSAIL 2019 Annual Project Review

Download ICS File 25/03/2019 ,

Executive Overview Sessions Open to publi Date: March 25, 2019 Time: 10:15AM - 5:15PM Venue: Hamad Bin Khalia Reseach Complex Multipurpose Room To view agenda, please click here . To RSVP to this ...

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"Learning to See" Public talk by Professor Antonio Torralba (MIT-CSAIL)

Download ICS File 25/03/2019 ,

Visit by Antonio Torralba, who teaches machines to automate tasks that a human visual system can accomplish, is part of annual spring research update between QCRI and MIT-CSAIL.

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News Releases

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QCRI and iMMAP announce Memorandum of Understanding

03/03/2019

Pact aims to apply data analysis and artificial intelligence techniques to solve humanitarian problems.

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UNDP partners with QCRI to use AI for social good

11/02/2019

Qatar forum on leveraging AI to solve humanitarian problems fills to capacity.

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Renowned computing expert C. Mohan to bust blockchain myths in Qatar talk

22/01/2019

Well-known inventor of database recovery algorithms to deliver keynote at QCRI's first blockchain workshop.

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