Conferences and Journals

• Hattatoglu, B., Qahtan, A., Kaya, H., Velegrakis, Y., ``SynthFair: Ensuring Subgroup Fairness in Classification via Synthetic Data Generation''}, accepted by (ICDATA'24) 
• Bannany, O., Qahtan, A., ``TGAIN: Missing Data Imputation for Mixed-Type Relational Datasets using Generative Adversarial Networks'', accepted by  (ICDATA'24)
• Tsiamis, T., Qahtan, A., ``FIONA: Detecting Syntactical Outliers in Attributes with Categorical Values'', accepted by (ICDATA'24)
• Zylinski, A., Qahtan, A., ``SynODC: Utilizing the Syntactic Structure for Outlier Detection in Categorical Attributes'', accepted by (ECML/PKDD'24)
• Huete, J., Qahtan, A., Hassani, M., ``PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees'', In the IEEE Computer Society Signature Conference on Computers, Software, and Applications, COMPSAC'23, June 27 - 29, 2023, Torino, Italy (Hybrid).
• Kampers, O., Qahtan, A., Mathur, S., Velegrakis, Y., "Manipulation detection in cryptocurrency markets: an anomaly and change detection based approach'', In the Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing SAC'22, April 25 - 29, 2022, Virtual.
• Qahtan, A., Tang, N., Ouzzani, M., Cao, Y., Stonebraker, M., "Pattern Functional Dependencies for Data Cleaning", In the 46th International Conference on Very Large Data Bases (PVLDB'20), August 31 - September 4, Tokyo, Japan, Vol. 13, No. 5, pp. 684-697
• Qahtan, A., Elmagarmid, A., Fernandez, R., Ouzzani, M., Tang, N., “FAHES: A Robust Disguised Missing Values Detector”, In the 24-th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’18), August 19-23, 2018, London, United Kingdom.
• Fernandez, R., Mansour, E., Qahtan, A., Elmagarmid, A., Ilyas, I., Madden, S., Ouzzani, M., Stonebraker, M., Tang, N., “Seeping Semantics: Linking Datasets using Word Embeddings for Data Discovery”, In the 34-th IEEE International Conference on Data Engineering (ICDE’18), April 16-19, 2018, Paris, France.
• 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) (IF: 3.857), Vol. 29, No. 3, 2017, pp. 642-655.
• Alharbi, B., Qahtan, A., Zhang, X., “Minimizing User Involvement for Learning Human Mo- bility Patterns from Location Traces”, In the 30-th AAAI Conference on Artificial Intelligence (AAAI’16), February 12-17, 2016, Phoenix, Arizona, USA.
• Qahtan, A., Alharbi, B., Wang, S., 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.
• Qahtan, A., Wang, S., Carroll, R. J., Zhang, X., “A New Study of Two Divergence Metrics for Change Detection in Data Streams”, In the 21-st European Conference on Artificial Intelligence (ECAI’14), August 18-22, 2014, Prague, Czech Republic.
• Qahtan, A., Zhang, X., 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.
• Salah, K. and Kahtani, A., “Performance Evaluation Comparison of Snort NIDS under Linux and Windows Server”, Journal of Network and Computer Applications (IF(2024): 7.7), Vol. 33, No. 1, 2010.
• Salah, K. and Qahtan, A., “Implementation and Experimental Performance Evaluation of a Hybrid Interrupt-Handling Scheme”, Journal of Computer Communications (IF(2024): 4.5), Vol. 32, No. 1, 2009.
• Salah, K. and Kahtani, A., “Improving Snort Performance under Linux”, Journal of IET Communications (IF(2022): 1.6), Vol. 3, No. 12, 2009.

Demos

• Zylinski, A., Qahtan, A., “DetCat: Detecting Categorical Outliers in Relational Datasets”, In the Conference on Information and Knowledge Management (CIKM'24), October 21-25, 2024, Boise, Idaho, USA.
• Qahtan, A., Tang, N., Ouzzani, M., Cao, Y., Stonebraker, M., “ANMAT: Automatic Knowledge Discovery and Error Detection through Pattern Functional Dependencies”, In the 2019 ACM SIGMOD Conference (SIGMOD'19), June 30 - July 5, Amsterdam, Netherlands.
• Qahtan, A., Elmagarmid, A., Ouzzani, M., Tang, N., “FAHES: Detecting Disguised Missing Values”, In the 34-th IEEE International Conference on Data Engineering (ICDE’18), April 16-19, 2018, Paris, France.
• Mansour, E., Deng, D., Fernandez, R., Qahtan, A., Tao, W., Abedjan, Z., Elmagarmid, A., Ilyas, I., Madden, S., Ouzzani, M., Stonebraker, M., Tang, N., “Building Data Civilizer Pipelines with an Advanced Workflow Engine”, In the 34-th IEEE International Conference on Data Engineering (ICDE’18), April 16-19, 2018, Paris, France.
• Fernandez, R., Deng, D., Mansour, E., Qahtan, A., Tao, W., Abedjan, Z., Elmagarmid, A., Ilyas, I., Madden, S., Ouzzani, M., Stonebraker, M., Tang, N., “A Demo of the Data Civilizer System”, In the 2017 ACM SIGMOD Conference (SIGMOD’17), May 14-19, Chicago, IL USA.

Book Chapters

• Qahtan, A., ``Machine Learning—Evaluation (Cross-validation, Metrics, Importance Scores...)'',  In Book: Clinical Applications of Artificial Intelligence in Real-World Data, pp.175-187
• Qahtan, A., Wang, S., Zhang, X., “Efficient Estimation of Dynamic Density Functions with Applications in Data Streams: Methods and Applications”, In Book: Learning from Data Streams in Evolving Environments, pp.247-278.