Mustansar Ali Ghazanfar

Dr. Mustansar Ghazanfar

Lecturer

Computer Science And Informatics

Department of Engineering & Computing , School of Architecture, Computing and Engineering

Dr Mustansar Ali Ghazanfar has served as a lecturer in the Department of Computer Science and Digital Technologies since 2018. He successfully introduced a new course and he is the programme leader for MSc Artificial Intelligence (2020). 

On This Page

OVERVIEW

Dr Mustansar Ali Ghazanfar has served as a lecturer in the Department of Computer Science and Digital Technologies since 2018. He successfully introduced a new course and he is the programme leader for MSc Artificial Intelligence (2020). The programme attracted 12 students in the first batch. He delivers lecturers related to Data Mining, Data Bases, Big Data, Artificial Intelligence, and Machine Learning. He supervises various BSc, MSc and PhD students.

RESEARCH

  • Data Mining, Machine/Deep Learning, Pattern Recognition: Recommender Systems, Collaborative Filtering, Information Retrieval, Kernel based learning, Classification techniques, Dimensionality reduction techniques for handling large scale data, Clustering, Neural Nets, Social Media Analysis, Cognitive Science, Web Mining and Analysis, NLP, Software agents, coalition formation in agents, multi-agent systems, search engines.
  • Forecasting, Personalization, Prediction, Decision Support Systems, Stock market prediction, Time series. 
  • Big Data, Business Intelligence & Insights, Machine Learning in Big Data. 
  • Launching new initiatives implementation, Vision, E-Govt, Consultancy, Digital Economy, Socio-economic development.

PUBLICATIONS

  • A novel centroid initialisation for kmeans clustering in the presence of benign outliers
    Amin Karimi, Shafiq Rehman, Mustansar Ali Ghazanfar. 2020. International Journal of Data Analysis Techniques and Strategies.
  • An improved product recommendation method for collaborative filtering
    Arta Iftikhar, Mustansar Ali Ghazanfar, Mubbashir Ayub, Zahid Mehmood, Muazzam Maqsood. 2020. IEEE Access (Accepted).
  • Stock market prediction using machine learning classifiers and social media, news
    Wasiat Khan, Mustansar Ali Ghazanfar, Muhammad Awais Azam, Amin Karami, Khaled H Alyoubi, Ahmed S Alfakeeh. 2020. Journal of Ambient Intelligence and Humanized Computing, Pages 1-24.
  • An Effective Model for Jaccard Coefficient to Increase the Performance of Collaborative Filtering
    Mubbashir Ayub, Mustansar Ali Ghazanfar, Tasawer Khan, Asjad Saleem. 2020. Arabian Journal for Science and Engineering.
  • Unifying user similarity and social trust to generate powerful recommendations for smart cities using collaborating filtering-based recommender systems
    Mubbashir Ayub, Mustansar Ali Ghazanfar, Zahid Mehmood, Khaled H Alyoubi, Ahmed S Alfakeeh. 2019. Soft Computing, Pages 1-24 Publisher Springer Berlin Heidelberg.
  • Predicting stock market trends using machine learning algorithms via public sentiment and political situation analysis
    Wasiat Khan, Usman Malik, Mustansar Ali Ghazanfar, Muhammad Awais Azam, Khaled H. Alyoubi, Ahmed S. Alfakeeh. 2019. Soft Computing, Springer Berlin Heidelberg, ISSN 1432-7643, pp 1-25.
  • Modelling user rating preference behaviour to improve the performance of the collaborative filtering-based recommender systems
    Mubbashir Ayub, MA Ghazanfar, Zahid Mehmood, Tanzila Saba, Riad Alharbey, Asmaa Mahdi Munshi, Mayda Abdullateef Alrige. 2019. PloS one, Volume 14, Issue 8, Pages e0220129.
  • Mispronunciation Detection Using Deep Convolutional Neural Network Features and Transfer Learning-Based Model for Arabic Phonemes
    Faria Nazir, Muhammad Nadeem Majeed, MA Ghazanfar, Muazzam Maqsood. IEEE Access, volume 7, 52589-52608.
  • Kernel Context Recommender System (KCR): A Scalable Context-Aware Recommender System Algorithm
    Misbah Iqbal, MA Ghazanfar, Asma Sattar, Muazzam Maqsood, Salabat Khan, Irfan Mehmood, Sung Wook Baik. 2019. IEEE Access, 2019, Volume 7, Pages 24719-24737.
  • Social media signal detection using tweets volume, hashtag, and sentiment analysis
    Faria Nazir, MA Ghazanfar, Muazzam Maqsood, Farhan Aadil, Seungmin Rho, Irfan Mehmood. 2019. Multimedia Tools and Applications, volume 78, Issue 3, 2019.
  • An IoT based efficient hybrid recommender system for cardiovascular disease
    Fouzia Jabeen, Muazzam Maqsood, MA Ghazanfar, Farhan Aadil, Salabat Khan, Muhammad Fahad Khan, Irfan Mehmood. Journal Peer-to-Peer Networking and Applications, Springer US, Pages 1-14.
  • Optimized Gabor Feature Extraction for Mass Classification Using Cuckoo Search for Big Data E-Health Care
    Salabat Khan, Amir Khan, Muazzam Maqsood, MA Ghazanfar, Farhan A. Journal of Grid Computing, Volume 17, Issue 2, Pages 239-254 .
  • A Performance Comparison of Machine Learning Classification Approaches for Robust Activity of Daily Living Recognition
    Rida Ghafoor, MA Ghazanfar, M Awais Azam, Usman Nameem. Artificial Intelligence Review 21 (2), Pages 279-310.
  • A Dimensionality reduction based efficient software fault prediction using Fisher linear discriminant analysis (FLDA)
    A Kalsoom, M Maqsood, MA Ghazanfar, F Aadil, S Rho. The Journal of Supercomputing, Volume 74, Issue 9, Pages 4568-4602 (IF=2).
  • A Robust Regression-Based Stock Exchange Forecasting and Determination of Correlation between Stock MarketsUmair Khan, Farhan Aadil, MA Ghazanfar, Salabat Khan, Noura Metawa, Khan Muhammad, Irfan Mehmood, Yunyoung Nam. Sustainability, Volume 10, Issue 10, Pages 3702.
  • Scalable and Practical One-Pass Clustering Algorithms for Recommender System
    A Khalid, MA Ghazanfar, MA Azam, YF Aldhafiri, S Zahra. Intelligent Data Analysis 21 (2), 279-310.
  • Building Accurate and Practical Recommender System Algorithms Using Machine Learning Classifier and Collaborative Filtering
    A Sattar, MA Ghazanfar, M Iqbal. Arabian Journal for Science and Engineering 42 (8), 3229-324.
  • Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining
    S Nasreen, MA Azam, U Naeem, MA Ghazanfar, A Khalid. Arabian Journal for Science and Engineering.
  • Novel Centroid Selection Algorithms for K-Means Clustering in Recommender Systems
    S Zahra, MA Ghazanfar, A Khalid, MA Azam, U Naeem, A Prugel-Bennett. Information Sciences 320, 156-189.
  • Experimenting Switching Hybrid Recommender Systems 
    MA Ghazanfar. Intelligent Data Analysis 19 (4), 845-877.
  • Leveraging Clustering Approaches to Overcome Gray-Sheep Users Problem in Recommender Systems
    MA Ghazanfar, A Prügel-Bennett. Expert System with Application 41 (7), 3261-3275.
  • The Advantage of Careful Imputation Sources in Sparse Data-Environment of Recommender Systems: Generating Improved SVD-based Recommendations
    MA Ghazanfar, A Prügel-Bennett. Informatica 37 (2013) 61–92.
  • Kernel-mapping recommender system algorithms
    Mustansar Ali Ghazanfar, Adam Prügel-Bennett, Sandor Szedmak. Information Sciences, volume 208, page, 81-104.
  • A Comparative Study of Classifier Based Mispronunciation Detection System for Confusing Arabic phoneme
    M Maqsood, HA Habib, SM Anwar, MA Ghazanfar, T Nawaz. The Nucleus 54 (2).
  • Variance Based Pattern Detection for Inferring Activities of Daily Living
    W Ali, MA Azam, U Naeem, MA Ghazanfar, A Khalid, Y Amin. The Nucleus 54 (2).