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Dr. Fawad Hussain

Associate Professor (HEC Approved PhD Supervisor)
Qualifications: PhD in Machine Learning (Grenoble, France); MS Computer Science (Paris, France);
Research Interests: Machine Learning, Big Data Analysis, Data Mining, Artificial Intelligence, Semantic Analysis
Telephone: (Ext. 2396)


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 1st position at the intermediate level.

Dr. 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 .

His current areas of research interest include

  • Big data analysis 
  • Artificial Intelligence
  • Data and text mining
  • Bio-informatics
  • Machine learning (including algorithm development)
  • 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 Recieved

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

7.       HEC Best University Teacher Award (BUTA) - 2015

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.       1st Position in Group, BSISE Sargodha

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

Invited/Technical Talks Given

8.  Detecting fake trends in Twitter in an era of fake news, IEEE International Multi-topic Conference (INMIC), Islamabad, Inivited Speaker [2019] 

7.  Artificial Intelligence Research Directions, Artificial Intelligence Forum at the 4th Forum on China-Pakistan Scientific and Technology and Economic Cooperation, Beijing, China, Invited Talk [2019] 

6.   Revised Computer Science Curriculum, 3-Day HEC Curriculum based Workshop on Computer Science, Resource Person  [2018] 

5.  Research Methodologies, Graduate Students Society, Invited Talk [2017] 

4.  Multi-view clustering: Algorithms and Applications, IEEE International Conference on Frontiers of IT (FIT 2015), Islamabad, Invited Speaker [2015]

3.  Literature Review, Citation, and Referencing, Technical Workshop, GIK Institute [2013]

2.  Recent Trends in Machine Learning, HEC Workshop on Emerging trends in Computational Sciences, Invited Talk, PAK [2013]

1.  Co-Clustering and its applications, Seminar,  Air University, PAK [2011]

Selected Publications

♦ 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)
[Download Link]

♦ Munir B., Hussain S.F., and Noor A.: "Speeding up the patch ordering method for image denoising", Multimedia Tools and Applications (Springer), in press, Available online 8 May 2019. (2019)
[Download Link]

♦ Hussain S.F.: " Hussain, Syed Fawad. "A novel robust kernel for classifying high-dimensional data using Support Vector Machines", Expert Systems with Applications (Elsevier), volume 131, pages 116-131 (2019)
[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),  Available online 5 September 2018. 
[Download Link]

♦ Hussain S.F., and Iqbal S.: " CCGA: Co-Similarity based co-clustering using Genetic Algorithms", Applied Soft Computing (Elsevier), volume 82, pages 30-42, (2018) [Download Link]

♦ Hussain S. F., and Ramazan M.: "Biclustering of human cancer microarray data using co-similarity based co-clustering", Expert Systems with Applications (Elsevier), volume 55, pages 520-531, (2016)  
[Download Link]

♦ Hussain S. F. and Suryani A.: "On retrieving intelligently plagiarized documents using semantic similarity", Engineering Applications of Artificial Intelligence (Elsevier), volume 45, pages 246-258, (2015).
[Download Link]

♦ Hussain S. F. and Bashir S.: “Co-clustering of Multi-View Datasets", Knowledge and Information Systems (Springer), pages 1-26, (2015).  
[Download Link]

♦ Halim Z., Waqas M. and Hussain S. F.: “Clustering Large Probabilistic Graphs using Multi-Population Evolutionary Algorithm", Information Sciences (Elsevier), volume 317, pages 78-95, (2015).  
[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, Issue 1, Page 81-99, (2014
[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)
[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)
[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

♦  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)
[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)
[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)
[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)
[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)
[Download Link]


  1. 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]
  2. 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]



  • 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)


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


  • Machine Learning (600 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


  • 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)


  • Knowledge-Based Systems (KBS) published by Elsevier (IF 3.325)
  • Natural Computing published by Springer (IF 1.310)
  • IEEE Access published by IEEE (IF 1.27)
  • Engineering Applications of Artificial Intelligence published by Elsevier (IF 3.526)


  • HEC National Research Program for Universities (NRPU)
  • Pakistan Science Foundation (PSF)
  • HEC National Curriculum Revision Committee
  • International Collegiate Programming Competition (ICPC) - Chief Judge



        Chi-SIm Co-clustering
        Improved Co-Similarity Measure


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
Note: I am not the author of these datasets. Therefore, you are advised to follow any copyright protection/citation requirement as might be listed by the respective authors on their webpage. I simply maintain a list to these collections. Please feel free to let me know if any link is broken so it can be updated.

Graduate Students

  • Mr. Sherjeel Sikandar
    • Thesis
    • Status: In progress
  • Mr. Mohsin Khan Jadoon
    • Thesis: Multi-view classification
    • Status: In progress
  • Ms. Maryam Mir
    • Thesis: Machine learning for intrusion detection
    • Status: graudated
  • Ms. Naila Rahman
    • Thesis: Prediction and minimization of geometrical errors in incremental sheet forming process using ANN and GA
    • Status: graduated
  • Ms. Khadija Khan
    • Thesis: Improved Weighted Multi-view Clustering with Feature Selection
    • Status: graduated
  • Mr. Ali Shaukat
    • Thesis: Detection of Fake Twitter Trends and their Culprits
    • Status: graduated
  • Mr. Muhammad Haris
    • Thesis: Multi-View Co-Clustering Using an Improved k-means Algorithm
    • Status: graduated
  • Ms. Ifra Arif Butt
    • Thesis: Clustering Probabilistic Graphs using Ant Colony Optimization Approach
    • Status: graduated
  • Ms. Fatimah Shahzadi
    • Thesis: Feature Selection for Text Categorization
    • Status: graduated
  • Ms. Iffat Maab
    • Thesis: Clustering Probabilistic Graphs
    • Status: graduated
  • Mr. Zaheer Babar
    • Thesis: A Fast, Non-Redundant Feature Selection Method
    • Status: graduated
  • Mr. M. Asif Suryani
    • Thesis: Smart Plagiarism Detection Using Semantic Kernels
    • Status: graduated
  • Mr. Muhammad Mushtaq
    • Thesis: Multi-View Clustering via Ensemble Methods
    • Status: graduated
  • Mr. Bicktash Ali
    • Thesis: Personalized Spam Email Filtering
    • Status: graduated

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