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PhD Graudate Publications

2013-2014 PhD Graduates
Artur Abdullin, Data Scientist, Resonate
Abdullin, A., & Nasraoui, O. (2012, October). A Semi-supervised Learning Framework to Cluster Mixed Data Types. In KDIR (pp. 45-54).

Abdullin, A., & Nasraoui, O. (2012, October). Clustering heterogeneous data sets. In Web Congress (LA-WEB), 2012 Eighth Latin American (pp. 1-8). IEEE.

Abdullin, A., & Nasraoui, O. (2012, January). Clustering heterogeneous data with mutual semi-supervision. In String Processing and Information Retrieval (pp. 18-29). Springer Berlin Heidelberg.

Zurada, J. M., Mazurowski, M. A., Ragade, R., Abdullin, R., Wojtudiak, J., & Gentle, J. (2009). Building virtual community in computational intelligence and machine learning. IEEE Computational Intelligence Magazine, 4(1), 43-46.

Abdallah Abd Elghafar Mohamed  

Khan Mohammed  
2012-2013 PhD Graduates
Brent Wenerstrom, Software Development Engineer, Amazon
Wenerstrom, B., & Giraud-Carrier, C. (2006, December). Temporal data mining in dynamic feature spaces. In Data Mining, 2006. ICDM'06. Sixth International Conference on (pp. 1141-1145). IEEE.

Kantardzic, M., Walgampaya, C., Wenerstrom, B., Lozitskiy, O., Higgins, S., & King, D. (2008, December). Improving click fraud detection by real time data fusion. In Signal Processing and Information Technology, 2008. ISSPIT 2008. IEEE International Symposium on (pp. 69-74). IEEE.

Kantardzic, M., Wenerstrom, B., Walgampaya, C., Lozitskiy, O., Higgins, S., & King, D. (2009). Time and space contextual information improves click quality estimation. e-COMMERCE 2009, 123.

Smith, M., Wenerstrom, B., Giraud-Carrier, C., Lawyer, S., & Liu, W. (2007). Personalizing E-Commerce with Data Mining. In E-Service Intelligence (pp. 273-286). Springer Berlin Heidelberg.

Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms. John Wiley & Sons.

Wenerstrom, B. (2009). Analysis of Emergency Room Waiting Time in SAS.

Wenerstrom, B., Kantardzic, M., Arabmakki, E., & Hindi, M. (2012, October). Multitweet summarization for flu outbreak detection. In AAAI Fall Symposium Series.

Kantardzic, M., Wenerstrom, B., Walgampaya, C., Higgins, S., & King, D. CLICK FRAUD DETECTION USING TIME AND SPACE CONTEXTUAL INFORMATION.

Wenerstrom, B. (2012). Enhanced web-based summary generation for search. University of Louisville.

Walgampaya, C., Kantardzic, M., & Wenerstrom, B. (2012). Duplicate detection in pay–per–click streams using temporal stateful Bloom filters. International Journal of Data Analysis Techniques and Strategies, 4(4), 340-377.

Wenerstrom, B., & Kantardzic, M. (2011). ReClose: web page summarization combining summary techniques. International Journal of Web Information Systems, 7(4), 333-359.

Wenerstrom, B., Ragade, R., & Kantardzic, M. (2012). ReClose Fuzz: Improved Automatic Summary Generation using Fuzzy Sets. ICSIIT 2012, 8.

Wenerstrom, B., & Kantardzic, M. (2011). Enhanced Visualization for Web-Based Summaries. In VLDS (pp. 40-45).

Wael Ali Emara  

Naouel Baili, Data Scientist, Quintiles

Mohamed, A. A., D'Souza, D., Baili, N., & Yampolskiy, R. V. (2011, December). Avatar face recognition using wavelet transform and hierarchical multi-scale LBP. In Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on (Vol. 1, pp. 194-199). IEEE.

Baili, N., & Frigui, H. (2011, June). Fuzzy clustering with multiple kernels. In Fuzzy Systems (FUZZ), 2011 IEEE International Conference on (pp. 490-496). IEEE.

Baili, N., & Frigui, H. (2012, June). Fuzzy clustering with multiple kernels in feature space. In Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on (pp. 1-8). IEEE.

Baili, N., & Frigui, H. (2011, December). Relational Fuzzy Clustering with Multiple Kernels. In Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on (pp. 488-495). IEEE.

Mohamed, A. A., D'Souza, D., Baili, N., & Yampolskiy, R. V. (2011). 2011 10th International Conference on Machine Learning and Applications and Workshops.

Frigui, H., Bchir, O., & Baili, N. (2013). An Overview of Unsupervised and Semi-Supervised Fuzzy Kernel Clustering. INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, 13(4), 254-268.

Basheer Zuhair Hawwash  

William Alan Mattingly  
2011-2012 PhD Graduates
Cyu Choon Cho  

Nurcan Durak, Rocket Scientist, Rocket Fuel, Inc. Google Scholar Profile

Fahim Mohammad, Machine Learning and Bioinformatics Researcher, Harvard University  

Selwyn Onyebuchi Igwe, Database Administrator Oracle/Project Manager, Louisville Water Company
Igwe, S. O. (2011). Medical image storage system for metadata-based retrieval. University of Louisville.

Dazhuo Li, Data Scientist, Cisco Systems  

Yehia Hassan Khalil Mohamed  

Chamila Kumara Walgampaya, Senior Lecturer, Faculty of Engineering, University of Peradeniya
Walgampaya, C. K. (2012). Click fraud: How to spot it, how to stop it?. University of Louisville.

Walgampaya, C., & Kantardzic, M. (2011, September). Cracking the smart clickbot. In Web Systems Evolution (WSE), 2011 13th IEEE International Symposium on (pp. 125-134). IEEE.

Walgampaya, C. K. (2006). Cost-benefit Analysis in Multiple Time Series Prediction (Doctoral dissertation, University of Louisville).

Walgampaya, C., Kantardzic, M., & Wenerstrom, B. (2012). Duplicate detection in pay–per–click streams using temporal stateful Bloom filters. International Journal of Data Analysis Techniques and Strategies, 4(4), 340-377.
2010-2011 PhD Graduates
Ouiem Bchir, Assistant Professor, KSU, Saudi Arabia
Zare, A., Bchir, O., Frigui, H., & Gader, P. (2010, June). Spatially-smooth piece-wise convex endmember detection. In Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on (pp. 1-4). IEEE.

Zare, A., Bchir, O., Frigui, H., & Gader, P. (2010, June). A comparison of deterministic and probabilistic approaches to endmember representation. In Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on (pp. 1-4). IEEE.

Bchir, O., Frigui, H., Zare, A., & Gader, P. (2010, June). Multiple model endmember detection based on spectral and spatial information. In Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on (pp. 1-4). IEEE.

Zare, A., Gader, P., Bchir, O., & Frigui, H. (2013). Piecewise convex multiple-model endmember detection and spectral unmixing. Geoscience and Remote Sensing, IEEE Transactions on, 51(5), 2853-2862.

Bchir, O., & Frigui, H. (2010, August). Fuzzy relational kernel clustering with local scaling parameter learning. In Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on (pp. 289-294). IEEE.

Alotaibi, S., Qasim, S., Bchir, O., & Ismail, M. M. B. (2013, January). Empirical Comparison of Visual Descriptors for Multiple Bleeding Spots Recognition in Wireless Capsule Endoscopy Video. In Computer Analysis of Images and Patterns (pp. 402-407). Springer Berlin Heidelberg.

Bchir, O., Frigui, H., Ismail, B., & Maher, M. (2013, June). Semi-supervised clustering and local scale learning algorithm. In Computer and Information Technology (WCCIT), 2013 World Congress on (pp. 1-5). IEEE.

Bchir, O., Frigui, H., & ISMAIL, M. M. B. (2013). Semi-Supervised Fuzzy Clustering with Learnable Cluster Dependent Kernels. International Journal on Artificial Intelligence Tools, 22(03).

Bchir, O. (2011). Unsupervised amd semi-supervised clustering with learnable cluster dependent kernels. University of Louisville.

Ahmed Chamseddine Ben Abdallah, Software Consultant, OptoPartner, Paris, France
Abdallah, A. C. B., Frigui, H., & Gader, P. (2012). Adaptive local fusion with fuzzy integrals. Fuzzy Systems, IEEE Transactions on, 20(5), 849-864.

Frigui, H., Gader, P. D., & Abdallah, A. C. B. (2008, April). A generic framework for context-dependent fusion with application to landmine detection. In SPIE Defense and Security Symposium (pp. 69531F-69531F). International Society for Optics and Photonics.

Frigui, H., Gader, P. D., & Abdallah, A. C. B. (2009, May). Context extraction for local fusion for landmine detection with multi-sensor systems. In SPIE Defense, Security, and Sensing (pp. 730328-730328). International Society for Optics and Photonics.

Frigui, H., Caudill, J., & Ben Abdallah, A. C. (2008, June). Fusion of multi-modal features for efficient content-based image retrieval. In Fuzzy Systems, 2008. FUZZ-IEEE 2008.(IEEE World Congress on Computational Intelligence). IEEE International Conference on (pp. 1992-1998). IEEE.

Abdallah, A., Frigui, H., & Gader, P. (2009, August). Context extraction for local fusion using fuzzy clustering and feature discrimination. In Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on (pp. 490-495). IEEE.

Abdallah, A. C. B. (2010). A Generic Framework for Context-dependent Fusion with Application to Landmine Detection (Doctoral dissertation, University Of Louisville).

Abdallah, A. C. B., Frigui, H., & Gader, P. (2010). Adaptive local fusion with neural networks. In Artificial Neural Networks–ICANN 2010 (pp. 486-491). Springer Berlin Heidelberg.

Ben Abdallah, A. C., Frigui, H., & Gader, P. (2010, July). Local Fusion with Fuzzy Integrals. In Fuzzy Systems (FUZZ), 2010 IEEE International Conference on (pp. 1-7). IEEE.

Mohamed Maher Ben Ismail, Assistant Professor, King Saud University, Riyadk
Ismail, B., & Maher, M. (2011). Image annotation and retrieval based on multi-modal feature clustering and similarity propagation. University of Louisville.

Alotaibi, S., Qasim, S., Bchir, O., & Ismail, M. M. B. (2013, January). Empirical Comparison of Visual Descriptors for Multiple Bleeding Spots Recognition in Wireless Capsule Endoscopy Video. In Computer Analysis of Images and Patterns (pp. 402-407). Springer Berlin Heidelberg.

Bchir, O., Frigui, H., Ismail, B., & Maher, M. (2013, June). Semi-supervised clustering and local scale learning algorithm. In Computer and Information Technology (WCCIT), 2013 World Congress on (pp. 1-5). IEEE.

Bchir, O., Frigui, H., & ISMAIL, M. M. B. (2013). Semi-Supervised Fuzzy Clustering with Learnable Cluster Dependent Kernels. International Journal on Artificial Intelligence Tools, 22(03).

Ismail, B., & Maher, M. (2012). Image Database Categorization based on a Novel Possibilistic Clustering and Feature Weighting Algorithm. International Proceedings of Computer Science & Information Technology, 46.

Bchir, O., Frigui, H., Ismail, B., & Maher, M. (2013, June). Semi-supervised relational fuzzy clustering with local distance measure learning. In Computer and Information Technology (WCCIT), 2013 World Congress on (pp. 1-4). IEEE.

Ismail, B., & Maher, M. (2012). Image Database Categorization based on a Novel Possibilistic Clustering and Feature Weighting Algorithm. International Proceedings of Computer Science & Information Technology, 46.

ISMAIL, M. M. B., & Bchir, O. (2012). AUTOMATIC IMAGE ANNOTATION BASED ON SEMI-SUPERVISED CLUSTERING AND MEMBERSHIP-BASED CROSS MEDIA RELEVANCE MODEL. International Journal of Pattern Recognition and Artificial Intelligence, 26(06).

Waleed Hassan El-Said Abd El Salam  

Robert Roy Kelley  

Jason Daron Meredith
Meredith, J. D. (2010). Adaptive constrained clustering with application to dynamic image database categorization and visualization. University of Louisville.

Viktoria Borisovna Rojkova, Senior Scientist, ID Analytics
Xie, J., Rojkova, V., Pal, S., & Coggeshall, S. (2009). A Combination of Boosting and Bagging for KDD Cup 2009-Fast Scoring on a Large Database. Journal of Machine Learning Research-Proceedings Track, 7, 35-43.

Rojkova, V., & Kantardzic, M. (2007). Delayed correlations in inter-domain network traffic. arXiv preprint arXiv:0707.1083.

Rojkova, V., Khalil, Y., Elmaghraby, A., & Kantardzic, M. (2007, December). Use of simulation and random matrix theory to identify the state of network traffic. In Signal Processing and Information Technology, 2007 IEEE International Symposium on (pp. 647-652). IEEE.

Rojkova, V., & Kantardzic, M. (2007). Analysis of inter-domain traffic correlations: Random matrix theory approach. arXiv preprint arXiv:0706.2520.

Rojkova, V., & Kantardzic, M. (2007, December). Feature extraction using random matrix theory approach. In Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on (pp. 410-416). IEEE.

Esin Saka, Applied Researcher, Microsoft Corporation
Nasraoui, O., Soliman, M., Saka, E., Badia, A., & Germain, R. (2008). A web usage mining framework for mining evolving user profiles in dynamic web sites. Knowledge and Data Engineering, IEEE Transactions on, 20(2), 202-215.

Saka, E., & Nasraoui, O. (2008, November). Simultaneous clustering and visualization of web usage data using swarm-based intelligence. In Tools with Artificial Intelligence, 2008. ICTAI'08. 20th IEEE International Conference on (Vol. 1, pp. 539-546). IEEE.

Nasraoui, O., Zhang, Z., & Saka, E. (2006, August). Web Recommender System Implementations in Multiple Flavors: Fast and (Care-) Free for All. In SIGIR Open Source Information Retrieval workshop (pp. 46-53).

Nasraoui, O., & Saka, E. (2007). Web usage mining in noisy and ambiguous environments: exploring the role of concept hierarchies, compression, and robust user profiles. In From Web to Social Web: Discovering and Deploying User and Content Profiles (pp. 82-101). Springer Berlin Heidelberg.

Saka, E., & Nasraoui, O. (2009). Improvements in flock-based collaborative clustering algorithms. In Computational Intelligence (pp. 639-672). Springer Berlin Heidelberg.

Saka, E., & Nasraoui, O. (2010, October). A recommender system based on the collaborative behavior of bird flocks. In Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2010 6th International Conference on (pp. 1-10). IEEE.

Saka, E., & Nasraoui, O. (2010, March). On dynamic data clustering and visualization using swarm intelligence. In Data Engineering Workshops (ICDEW), 2010 IEEE 26th International Conference on (pp. 337-340). IEEE.
2009-2010 PhD Graduates
Aleksey Yuryevich Ashikhmin, Data Scientist, Resonate Networks
Amenitskiy, A. V., Belov, A. A., Igumnov, L. A., & Litvinchuk, S. Y. COMPUTATIONAL CONTINUUM MECHANICS.

Brian S. Carter, Leader and Visionary, Software Solutions  

Noha Youssry El-Zehiry, Research Scientist, Siemens Corporate Research
El-Zehiry, N. Y., & Grady, L. (2010, June). Fast global optimization of curvature. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on (pp. 3257-3264). IEEE.

El-Zehiry, N. Y., & Elmaghraby, A. (2008). A graph cut based active contour for multiphase image segmentation. In ICIP (pp. 3188-3191).

El-Zehiry, N. Y., & Elmaghraby, A. (2007). Brain MRI tissue classification using graph cut optimization of the Mumford–Shah functional. In Proceedings of Image and Vision Computing, New Zealand (pp. 321-326).

El-Zehiry, N. Y. (2009). A graph cut framework for two dimensional/three dimensional implicit front propagation with application to the image segmentation problem. University of Louisville.

El-Zehiry, N. Y., & Grady, L. (2012, May). Vessel segmentation using 3D elastica regularization. In Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on (pp. 1288-1291). IEEE.

El-Zehiry, N. Y., & Grady, L. (2013). Combinatorial Optimization of the Discretized Multiphase Mumford–Shah Functional. International journal of computer vision, 104(3), 270-285.

Grady, L., & El-Zehiry, N. Y. (2013). U.S. Patent No. 8,478,044. Washington, DC: U.S. Patent and Trademark Office.

Aleksey Sergeyevich Fadeev, Data Scientist, Facebook  

Christy Marie Gearheart Bogard, Computational Scientist Postdoctoral Fellow, University of Colorado Denver
Gearheart, C. M. B. (2010). DNA-based computing for secure circuitry design (Doctoral dissertation, University of Louisville).

Cedric Joel Jeannot  

Nathan Patrick Johnson, University of Louisville  

Rami Nezar Mahdi
Mahdi, R. N. (2010). Reduced hyperbf networks: practical optimization, regularization, and applications in bioinformatics. University of Louisville.

Walid Oualid Missaoui  

Carlos Clemente Rojas  

Lijun Zhang, Postdoctoral Fellow, Penn State University  

Leyla Zhuhadar, Assistant Professor, Business Intelligence, Computer Information Systems, Gordon Ford College of Business, Western Kentucky University Google Scholar Profile
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