Dr. Abdulhakim Ali Qahtan

Postdoctoral researcher
Data Analytics

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Research Focus at QCRI

Abdulhakim Qahtan is currently a Post Doctoral Researcher at Qatar Computing Research Institute (QCRI), Hamad Bin Khalifa University, Qatar. Mr. Qahtan was awarded his PhD degree from the Machine Intelligence & Knowledge Engineering (MINE) Lab at King Abdullah University of Science and Technology (KAUST) in 2016.  He completed his B.S. and M.S. in Computer Science at Cairo University, Egypt (2000) and King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia (2008), respectively. He worked as a teaching assistant at Taiz University, Yemen (2001 – 2003) and a lecturer in KFUPM, Saudi Arabia (2008 – 2010).  

His research interests include:

- Large-scale data discovery

- Data cleaning

Previous Experience

Post Doctoral Researcher
Data Analytics Group, QCRI

Sep-Dec  2015
Teaching Assistant
KAUST, Saudi Arabia

Jul-Aug 2012
Texea A&M University, USA

Professional Experience

Professional Associations and Awards


PhD Computer Science - Dissertation Title: Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data.
King Abdullah University of Science and Technology (KAUST), Thuwal, KSA.  August 2010 - June 2016

M.S. Computer Science - Thesis Title: Implementation and Experimental Performance Evaluation of a Hybrid Interrupt-Handling Scheme.
King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, KSA. September 2003-June 2008

Bachelor in Computer Science (with honors)
Cairo University, Cairo, Egypt.  September 1996-June 2000.

Selected Research

- Fernandez, R., Deng, D., Mansour, E., Qahtan, A., Tao, W., Abedjan, Z., Elmagarmid, A., Ilyas, I. F., Madden, S., Ouzzani, M., Stonebraker, M., Tang, N.
“A Demo of the Data Civilizer System,”, the 2017 ACM SIGMOD Conference (SIGMOD'17), May 14-19, Chicago, IL USA.

- Qahtan, A., Wang, S. and Zhang, X.
“KDE-Track: An Efficient Dynamic Density Estimator for Data Streams,” the IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 29, No. 3, 2017, pp. 642-655.

- Alharbi, B., Qahtan, A., and Zhang, X.
“Minimizing User Involvement for Learning Human Mobility Patterns from Location Traces,” accepted by: the 30-th AAAI Conference on Artificial Intelligence (AAAI’16), February 12-17, 2016, Phoenix, Arizona, USA.

- Qahtan, A., Alharbi, B., Wang, S. and Zhang, X.
“A PCA-Based Change Detection Framework for Multidimensional Data Streams,” In the 21-st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’15), August 10-13, 2015, Sydney, Australia, pp. 935-944.

- Qahtan, A., Zhang, X. and Wang, S.
”Efficient Estimation of Dynamic Density Functions with an Application to Outlier Detection,” In the 21-st ACM International Conference on Information and Knowledge Management (CIKM’12), October 29 - November 02, 2012, Maui, HI, USA, pp. 2159-2163.

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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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Download ICS File 27/03/2018 ,

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QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

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