Prof. Dr. Fawad Hussain

Profile

Syed Fawad Hussain obtained his MS degree in Computer Science from the prestigious Pierre and Marie Curie University (now Paris-Sorbonne University), a top 50  ranked univeristy in the world (World Ranking #36), Paris, France, and a Ph.D. in Computer Science from the University of Grenoble (World Ranking #151-200), Grenoble, France. His area of research during his Ph.D. was Machine Learning and Artificial Intelligence in which he proposed new algorithms for finding similarity patterns in data. He was associated with the AMA team (now part of LIG Lab, Grenoble, France).

He has worked on various academic-industrial projects during his educational career. Prior to joining GIK Institute, he was associated with the TIMC Research Labs, where he was involved in research related to defining similarity measures in a linked graph with application to text mining for social media networking as part of a project partly funded by the French National Research Association and Xerox Research Europe.  During his MS research internship with the ERIC research labs in Lyon, France, he proposed a Personalized Health Anticipation Data Warehouse as a novel approach to healthcare management and preemptive response, mainly designed for the French National Football Team.

Dr. Fawad Hussain is an HEC approved PhD supervisor, a professional member of the Association for Computing Machinery (ACM), a senior member of Institute of Electrical and Electronics Engineers (IEEE), a member of the Higher Education Commission(HEC) of Pakistan National Curriculum Review Committee for Computer Science, a reviewer for the HEC National Research Project for Universities (NRPU) and the Pakistan Science Foundation (PSF). During his academic career, he has been awarded an HEC foreign scholarship for Ph.D., a Google/IBM Grant based on his publication at the SIAM Data Mining Conference (SDM 2010, USA), and merit certificates for 1^st position at the intermediate level.

Syed Fawad Hussain is recipient of multiple research and teaching awards. He was awarded the nationwide Best University Teacher Award (BUTA) for the year 2015 by the Higher Education Commission of Pakistan. The award is conferred on the basis of teaching, research and other scholarly work performed during the year 2015. At the institute level, he has been awarded the G.I.K Research Award. Dr. Fawad is a COMSTECH International Distinguished Scholar since 2021.

His current areas of research interest include

• Machine learning (including algorithm development)
• Data Science 
• Artificial Intelligence
• Bio-informatics
• Social media network analysis
• Deep learning (Deep neural networks)
• Interdisciplinary research (applying AI and machine learning in other disciplines such as mechanical engineering, signal processing, medical imaging, etc.)

Awards/Grants/Titles Received

11.      Distinguished International Scholar – COMSTECH

10.      G.I.K. Institute Best Research Award among all faculty members

9.       HEC Best University Teacher Award (BUTA) – 2015

8.       Professional Member (ACM)

7.       Senior Member (IEEE) 

6.       HEC Approved Ph.D. Supervisor 

5.       ICT RnD NGIRI funding 2013-14

4.       Google/IBM Grant  at the SIAM Data Mining Conference, Ohio, USA – 2010

3.       HEC Merit-based scholarship for Ph.D. – France

2.       1^st Position in Group, BSISE Sargodha

1.       1^st Position in College (Intermediate), Govt. College Sargodha

Invited/Technical Talks Given

1. Title: Multi-view learning: prospects and applications
   Type: Invited Speaker
   Venue: 47^th International Nathiagali Summer College (INSC), Nathiagali (Jun. 2022).
   Year:  2022
2. Title: Using Artificial Intelligence in Social Media Analytics
   Type: Invited Speaker
   Venue: 47^th International Nathiagali Summer College (INSC), Nathiagali (Jun. 2022).
   Year:  2022
3. Title: Data analytics in medical data
   Type: Invited Speaker
   Venue: Workshop on AI in Medicine, GIK Institute, December 16, 2021.
   Year:  2021
4. Title: Artificial Intelligence & its applications in engineering
   Type: Invited Speaker
   Venue: National Optics and Photonics Engineering Conference (NOPEC), 8-9 May 2021.
   Year:  2021
5. Title: Detecting fake news on Twitter
   Type: Invited Speaker
   Venue: 3^rd Pak-Turk International Conference on Emerging Technologies in the field of Sciences and Engineering.
   Year:  2020
6. Title: Artificial Intelligence Research Directions
   Type: Invited Speaker
   Venue: 4^th Forum on China-Pakistan Scientific and Technology and Economic Cooperation, Beijing, China.
   Year:  2019
7. Title: Detecting fake trends in Twitter in an era of fake news
   Type: Invited Speaker
   Venue: IEEE International Multi-topic Conference (INMIC)
   Year:  2019
8. Title: Revised Computer Science Curriculum
   Type: Resource Person
   Venue:  3-Day HEC Curriculum based Workshop on Computer Science, Islamabad
   Year:  2018
9. Title: Research Methodologies
   Type: Invited Speaker
   Venue: Graduate Students Society, GIK Institute
   Year:  2017
10. Title: Multi-view clustering: Algorithms and Applications
    Type: Invited Speaker
    Venue: IEEE International Conference on Frontiers of IT (FIT 2015), Islamabad
    Year:  2015
11. Title: Literature Review, Citation, and Referencing
    Type: Guest Speaker
    Venue:  Technical Workshop, GIK Institute
    Year:  2013
12. Title: Recent Trends in Machine Learning
    Type: Resource Person
    Venue: HEC Workshop on Emerging Trends in Computational Sciences, Topi
    Year:  2013

Selected Publications

This is a partial list of my publications. A more detailed list can be found at my Google Scholar Profile.

Book Chapter

♦ Hassan F., Hussain S. F.: “Machine Learning techniques for the classification of EEG signals”, Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning, Springer.  In Press
ISBN: . [Download Link]

♦ Qaiser S.M.*, Hussain S.F.: “Effective cardiac health diagnosis by using event-driven ECG processing with sub-bands features extraction and machine learning techniques”, Modelling and Analysis of Active Bio-potential Signals in Healthcare- Volume 2, IOP publishing, December 2020.
ISBN: 978-0-7503-3409-9. [Download Link]

Selected Peer-Reviewed Publications

2022

♦ Hassan F., Hussain S. F., Qaisar S. M.: “Epileptic Seizure Detection Using a Hybrid 1D CNN-Machine Learning Approach from EEG Data”, Journal of Healthcare Engineering, vol. 2022, 9579422 (2022). https://doi.org/10.1155/2022/9579422
[Journal paper, Impact Factor 3.822 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Hanif M., Tonazzini A., Hussain S. F., Habib U., Salerno E., Savino P., Halim Z.: “Blind bleed-through removal in color ancient manuscripts”, Multimedia Tools and Applications (2022). https://doi.org/10.1007/s11042-022-13755-6.
[Journal paper, Impact Factor 3.503 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Azam B., Khan M. J., Bhatti F. A., Maud A. R. M, Hussain S. F., Hashmi A. J., Khurshid K.: “Aircraft detection in satellite imagery using deep learning-based object detectors”, Microprocessors and Microsystems, vol. 94, 104630 (2022). https://doi.org/10.1007/s11042-022-13755-6.
[Journal paper, Impact Factor 2.577 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F., Shehzadi F., Munir B.: “Constrained Class-wise Feature Selection (CCFS)”, International Journal of Machine Learning and Cybernetics (Springer), accepted and to appear.
[Journal paper, Impact Factor 4.012 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Wang T., Liu Z., Zhang T., Hussain S. F., Waqas M., and Li Y.: “Adaptive feature fusion for time series classification”, Knowledge-Based Systems (Elsevier), accepted and to appear.
[Journal paper, Impact Factor 8.038 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F., Butt I. A., Hanif M., and Anwar S.: “Clustering Uncertain Graphs using Ant Colony Optimization (ACO)”, Neural Computing and Applications (Springer), accepted and to appear.
[Journal paper, Impact Factor 5.606 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F., Khan M., and Siddiqi I.: “Co-clustering based Classification of Multi-View Data”, Applied Intelligence (Springer), accepted and to appear.
https://doi.org/10.1007/s10489-021-03087-7
[Journal paper, Impact Factor 5.09 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F. and Qaiser S. M.: “Epileptic Seizure Classification Using Level-Crossing EEG Sampling and Ensemble of Sub-problems Classifier”, Expert Systems with Applications, vol. 191, article id 116356. (2022).
[Journal paper, Impact Factor 6.953 (JCR 2021), SJR Q1, HEC W Category] [Download Link]

2021

♦ Bano S.*, Hussain S. F.: “Prediction of Covid-19 and post Covid-19 patients with reduced feature extraction using Machine Learning Techniques”, 18th International Conference on Frontiers of Information Technology (FIT), Dec. 13–15, Islamabad, Pakistan. (2021).
[Conference paper, Core Rank: National] [Download Link]

♦ Mansha S.*, Khalid T., Kamiran F., Hussain M., Hussain S. F., and Yin H.: “GDFM: Gene vectors embodied deep attentional factorization machines for interaction prediction”, 30th ACM International Conference on Information and Knowledge Management (CIKM), Nov. 1–5, Gold Coast, Australia, to appear. (2021).
[Conference paper, Core Rank: A] [Download Link]

♦ Khan H., Hussain S.*, Hussain S. F., Gul S., Ahmad A., Ullah S.: “Multivariate modeling and optimization of Cr (VI) adsorption onto carbonaceous material via response surface models assisted with multiple regression analysis and particle swarm embedded neural network”, Environmental Technology and Innovation, Vol. 24, 101952, November 2021 (2021).
https://doi.org/10.1016/j.eti.2021.101952
[Journal paper, Impact Factor 5.263 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F.*, Hussain G., Rahman N.: “Artificial Neural Network modelling and optimization of elastic and an-elastic spring back in polymer parts produced through ISF”, International Journal of Advanced Manufacturing Technology, accepted and to appear (2021).
doi.org/10.1007/s00170-021-08054-7
[Journal paper, Impact Factor 3.226 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Qaiser S.M.*, Hussain S. F.: “An effective arrhythmia classification via ECG signal subsampling and mutual information based subbands statistical features selection”, Journal of Ambient Intelligence and Humanized Computing (Springer), In Press,
doi.org/10.1007/s12652-021-03275-w (2021)
[Journal paper, Impact Factor 7.104 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F.*, Khadija K., Jillani R.: “Weighted multi-view co-clustering (WMVCC) for sparse data”, Applied Intelligence (Springer), In Press, doi.org/10.1007/s10489-021-02405-3 (2021)
[Journal paper, Impact Factor 5.086 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F.*, Maab I.: “Clustering probabilistic graphs using neighbourhood paths”, Information Sciences (Elsevier), Volume 568, Pages 216-238. doi: https://doi.org/10.1016/j.ins.2021.03.057 (2021)
[Journal paper, Impact Factor 6.795 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Qaiser S.M.*, Hussain S. F.: “Effective Epileptic Seizure Detection by Using Level-Crossing EEG Sampling Sub-Bands Statistical Features Selection and Machine Learning for Mobile Healthcare”, Computer Methods and Programs in Biomedicine (Elsevier), Volume 203 (Part B),106034  (2021)
[Journal paper, Impact Factor 5.428 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

2020

♦ Hussain S. F.*, Pervaiz A, Hussain M.: “Co-clustering using Artificial Bee Colony (ABC) algorithm: a parallelizable approach”, Applied Soft Computing (Elsevier), Volume 97 (Part B), 106725. (2020)
[Journal paper, Impact Factor 6.725 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S. F.*, Babar M. Z., Khalil A., Jilani R., Hanif M., Khurshid K.: “A fast non-redundant feature selection technique for textual data”, IEEE Access, 8, pp. 181763-18178. (2020)
[Journal paper, Impact Factor 3.367 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Jillani R., Hussain S.F., and Kalva H.: “Multi-view clustering for fast intra mode decision in HEVC”, IEEE International Conference on Consumer Electronics, Jan. 4-6, 2020, Las Vegas, USA. (2020)
[Conference Paper] [Download Link]

♦ Qaiser S.M.*, Hussain S. F.: “Arrhythmia diagnosis by using signal-piloted ECG processing and sub-bands features extraction for mobile healthcare”, special issue on Biomedical Signal Processing for Disease Diagnosis, Sensors vol. 20, pp. 2252-2270. (2020)
[Journal paper, Impact Factor 3.576 (JCR 2020), SJR Q1, HEC W Category] [Download Link]

♦ Hussain F., Shabbir G., Ramzan M., Hussain S.F., Qazi S.,”Conformal vector fields of static spherically symmetric space-times in  gravity”, International Journal of Geometric Methods in Modern Physics, vo. 17 (8), pp. 2050120. (2020)
[Journal paper, Impact Factor 1.874 (JCR 2020)] [Download Link]

2019

♦ Munir B.*, Hussain S.F., and Noor A., “Speeding up the patch ordering method for image de-noising”, Multimedia Tools and Applications (Springer), Volume 78, Issue 16, pp 23639–23657. (2019)
[Journal paper, Impact Factor 2.31 (JCR 2019), SJR Q1, HEC W Category]  [Download Link]

♦ Hussain S.F.*, “A novel robust kernel for classifying high-dimensional data using Support Vector Machines”, Expert Systems with Applications (Elsevier), Volume  131, pp 116-13. (2019)
[Journal paper, Impact Factor 5.45 (JCR 2019), SJR Q1, HEC W Category]  [Download Link]

♦ Hussain S.F.* and Haris M., “A k-means based Co-Clustering (kCC) algorithm for sparse, high dimensional data”, Expert Systems with Applications (Elsevier),  Volume 118, pp 20-34. (2019)
[Journal paper, Impact Factor 5.45 (JCR 2019), SJR Q1, HEC W Category] [Download Link]

Pre-2018

♦ Hussain S.F.* and Iqbal S., “CCGA: Co-clustering using Genetic Algorithms”, Applied Soft Computing (Elsevier), Volume 72, pp 30-42. (2018)
[Journal paper, Impact Factor 4.873 (JCR 2018), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S.F.*, and Ramazan M.: “Bi-clustering of human cancer microarray data using co-similarity based co-clustering”, Expert Systems with Applications  (Elsevier), Volume 55, pp 520–531. (2016)
[Journal paper, Impact Factor 3.928 (JCR 2016), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S.F.* and Suryani A.: “Using semantic kernels for detecting intelligent plagiarism in documents”, Engineering Applications of Artificial Intelligence  (Elsevier), Volume 45 (C), pp 246-258. (2015)
[Journal paper, Impact Factor 2.894 (JCR 2015), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S.F.* and Bashir S.: “Co-clustering of multi-view datasets”, Knowledge and Information Systems (Springer), Volume 47(3), pp 545–570. (2015)
[Journal paper, Impact Factor 2.004 (JCR 2015), SJR Q1, HEC W Category] [Download Link]

♦ Halim Z.*, Waqas M., and Hussain S.F.: “Clustering large probabilistic graphs”, Information Sciences (Elsevier), Volume 317, pp 78-95. (2015)
[Journal paper, Impact Factor 4.832 (JCR 2015), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S.F.*, Mushtaq M., and Halim Z.: “Multi-view document clustering via ensemble methods”, Journal of Intelligent Information Systems (Springer), Volume 43(1), pp 81-99. (2014)
[Journal paper, Impact Factor 1.00 (JCR 2014), SJR Q1, HEC W Category] [Download Link]

♦ Hussain S.F. : “Bi-Clustering Gene Expression Data Using Co-Similarity”, in Proceedings of the 7th International Conference on Advanced Data Mining and Applications (ADMA), 16-19th Dec. 2011, Beijing, China. pp 190-200. (2011)
[Conference paper, Core Rank: B] [Download Link]

♦  Hussain S.F., Grimal C., Bisson G. : “An improved Co-Similarity Measure for Document Clustering”, 9th IEEE International Conference on Machine Learning and Applications (ICMLA), 12-14th Dec. 2010, Washington D.C, pp 190-197, (2010)
[Conference paper, Core Rank: C] [Download Link]

♦ Hussain S. F. and Bisson G. : “Une approche générique pour la classification supervisée et non-supervisée de documents“, Conference Francophone pour l’Apprentissage Automatique (CAP), Clermont-Ferrand, France, 17-19 May, (2010)
[Conference paper] [Download Link]

♦  Hussain F. and Bisson G. : “Text Categorization using Word Similarities Based on Higher Order Co-Occurrences”, Society for Industrial and Applied Mathematics (SIAM) International Conference on Data Mining (SDM 2010), April 29-May 1, Columbus, Ohio, pp 1-12. (2010)
[Conference paper, Core Rank: A] [Download Link]

♦ Bisson G., Hussain F. : “Co-classification : méthode et validation ”, In 11ème Conférence Francophone sur l’apprentissage automatique (CAp 2009), Plate-forme AFIA, Hammamet, Tunisie, 26-29 Mai, 2009. Editions Cépaduès. (2009)
[Conference paper] [Download Link]

♦ Bisson G., Hussain S.F. : “X-sim: A new similarity measure for the co-clustering task”, 7th IEEE International Conference on Machine Learning and Applications (ICMLA), 11-13th Dec. 2008, San Diego, pp 211-217. (2008)
[Conference paper, Core Rank: C] [Download Link]

♦ Hussain, J., Rashid, K., Ahmad, H. F., Hussain S.F., “Effective Software Management– Where Do We Falter? “, Proceedings of the 6th International Conference on Software Engineering, Parallel and Distributed Systems(SEPAD), Corfu Island, Greece, 2007, pp. 13-17. (2007)
[Conference paper] [Download Link]

♦ Hussain J., Rashid Khalid, Ahmad H. Farooq, Hussain S.F., “A Stepwise Approach to Managing Software Projects“, Transactions on Computers Research, Vol. 2, no. 2, 2007. pp. 362-368 (2007)
[Journal Paper] [Download Link]

Theses

♦ Hussain, S.F. “A New Co-Similarity Measure: Application to Text Mining and Bio-Informatics”, PhD Thesis, TIMC Research Lab, University of Grenoble, FRANCE
[Download Link]

♦ Hussain, S.F. “Modeling Complex Data in the MAP Datawarehouse“, MS Research Thesis, ERIC Research Lab, Department of Computer Science, Pierre and Marie Curie University, Paris, FRANCE.
[Download Link]

Teaching

Undergraduate

• Advanced Databases (400 Level)
• Applied Artificial Intelligence (400 Level)
• Bio-Inspired Computing (400 Level)
• Data Warehousing and Data Mining (400 Level)
• Introduction to Artificial Intelligence (300 Level)  –
• Databases -1 (300 Level)
• Object-Oriented Programming (200 Level)
• Introduction to Computing (100 Level)

Labs

• Introduction to Artificial Intelligence Lab (300 Level)
• Databases -1 Lab (300 Level)
• Object-Oriented Programming Lab (200 level)

Graduate

• Machine Learning (600 Level)
• Stochastic Processes (500 Level)
• Pattern Recognition (500 Level)
• Big Data Analysis (500 Level)
• Advanced Algorithms and Computation (500 Level)

Scholarly Activities

I am /have been on the technical review committee of the following Conferences/Journals/Panels

Conferences

• International Conference on Emerging Technologies (ICET)
• IEEE International Conference on Frontiers of Information Technology (FIT)
• IEEE International Conference on Open Source Systems & Technologies (ICOSST)
• IEEE International Multi-topic Conference (INMIC)

Journals 

• Knowledge-Based Systems (KBS) published by Elsevier (IF 3.325)
• Expert Systems With Applications (ESWA) published  by Elsevier (IF 5.45)
• Applied Soft Computing (ASOC) published  by Elsevier (IF 5.47)
• Natural Computing published by Springer (IF 1.310)
• IEEE Access published by IEEE Society (IF 3.745)
• Engineering Applications of Artificial Intelligence (EAAI) published by Elsevier (IF 4.2)

Panels

• Reviewer, HEC National Research Program for Universities (NRPU)
• Member Technical, Pakistan Science Foundation (PSF)
• Reviewer, Double Helix Projects, Pakistan Science Foundation (PSF)
• Vice-Chair (CS), HEC National Curriculum Revision Committee (NCRC)
• Chief Judge, International Collegiate Programming Competition (ICPC)

Software/Datasets

Software

• Description: A matlab based code to co-cluster data using Chi-Sim co-similarity measure and Hierarchical clustering (Ward’s linkage)
• Download Link
• Reference Paper to Cite: Bisson G., Hussain F. : “X-sim: A new similarity measure for the co-clustering task”,  7th IEEE International Conference on Machine Learning and Applications (ICMLA), 11-13^th Dec. 2008, San Diego, United States.

• Description: Matlab Code for Semantic Similarity computation
• Download Link
• Reference Paper to Cite; Hussain S.F., Grimal C., Bisson G. : “An improved Co-Similarity Measure for Document Clustering”, 9th IEEE International Conference on Machine Learning and Applications (ICMLA), 12-14th Dec. 2010, Washington, United States.

Dataset

I maintain a list of popular datasets used in the general area of machine learning/data mining. Mostly, these are the datasets of interest to me. This page contains a link to some of the datasets

• Some of these data sets are in raw (text file) format without pre-processing (stop word removal, stemming, etc).
• Others are in the pre-processed format (usually matlab .mat files) as ready to use data for those who prefer not to go into the gritty of cleansing the data.
• Dataset include
  • Text data
  • Gene expression data
  • Faces data
  • Handwriting recognition data

Graduate Students

20.  Mr. Muhammad Haris (Ph.D. candidate, in co-supervision with Dr. Azlan, UTM Malaysia) 

• Thesis: Multi-view learning
• Status: in-progress

19.  Mr. Usman Haider (Ph.D. candidate, in co-supervision with Dr. Hanif, GIK Institute) 

• Thesis: Using dictionary models in deep learning
• Status: in-progress

18.  Mr. Haseeb Aslam 

• Thesis: 
• Status: in-progress

17.  Ms. Sabahat Durrani 

• Thesis: Application of deep learning algorithms
• Status: in-progress

16.  Ms. Fatima Hassan 

• Thesis: Analysis and classification of medical data
• Status: in-progress

15.  Ms. Zaib-un-Nisa 

• Thesis: Optimizing Co-clustering of Multi-View Data
• Status: graduated

14.  Mr. Muhammad Sherjeel 

• Thesis: Classification of ECG and EEG Signals using Machine Learning Methods
• Status: graduated

13.  Mr. Mohsin Khan Jadoon

• Thesis: Multi-View Classification
• Status: graduated

12.  Ms. Maryam Mir

• Thesis: Machine Learning for Intrusion Detection
• Status: graduated

11.  Ms. Naila Rahman

• Thesis: Prediction and Minimization of Geometrical Errors in Incremental Sheet Forming Process using ANN and GA
• Status: graduated

10.  Ms. Khadija Khan

• Thesis: Improved Weighted Multi-View Clustering with Feature Selection
• Status: graduated

9.   Mr. Ali Shaukat

• Thesis: Detection of Fake Twitter Trends and their Culprits
• Status: graduated

8.   Mr. Muhammad Haris

• Thesis: Multi-View Co-Clustering Using an Improved k-means Algorithm
• Status: graduated

7.   Ms. Ifra Arif Butt

• Thesis: Clustering Probabilistic Graphs using Ant Colony Optimization Approach
• Status: graduated

6.   Ms. Fatimah Shahzadi

• Thesis: Feature Selection for Text Categorization
• Status: graduated

5.   Ms. Iffat Maab

• Thesis: Clustering Probabilistic Graphs
• Status: graduated

4.   Mr. Zaheer Babar

• Thesis: A Fast, Non-Redundant Feature Selection Method
• Status: graduated

3.   Mr. M. Asif Suryani

• Thesis: Smart Plagiarism Detection Using Semantic Kernels
• Status: graduated

2.   Mr. Muhammad Mushtaq

• Thesis: Multi-View Clustering via Ensemble Methods
• Status: graduated

1.   Mr. Bicktash Ali

• Thesis: Personalized Spam Email Filtering
• Status: graduated