Dr. Essam Mansour

Essam Mansour pic.jpg
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 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 at the International University in Germany Bruchsal from July 2008 to October 2009, and in King Abdullah University of Science and Technology (KAUST) from October 2009 to Jun 2013. Dr. Mansour joined Qatar Computing Research Institute (QCRI) as a Senior Research Software Engineer in June, 2013.

Dr. Mansour's research interests include database systems, large-scale data analytics, web data management, parallel/distributed systems and machine learning. 

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

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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MIT/QCRI system uses machine learning to build road maps

22/04/2018

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Upcoming Events

Past Events

2018

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QCRI Summer Internship Program

Download ICS File 06/05/2018  - 05/07/2018 , Hamad Bin Khalifa Research Complex

Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.

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Regina

Public Talk by Prof. Regina Barzilay "Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text"

Download ICS File 27/03/2018 ,

Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...

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QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

Executive Overview Sessions Open to public Date:    Tuesday, March 27, 2018 Time:    9:00AM – 3:00PM Venue:  HBKU Research Complex Multipurpose Room To view full agenda, please click here . To RSVP, ...

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News Releases

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QCRI announces 2018 summer camps for kids

09/07/2018

Register soon as places fill quickly.

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QCRI to launch Qatar Center for Artificial Intelligence (QCAI)

14/05/2018

Initiative plans to ramp up development of artificial intelligence technologies to position Qatar as a global leader in AI.

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QCRI hosts humanitarian data skills workshop

09/05/2018

Joint event with UNOCHA's Centre for Humanitarian Data, the Qatar Red Crescent Society and Education Above All Foundation held to devise common practices for data use in humanitarian action.

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