Dr Azhar Mahmood

Azhar Mahmood

Senior Lecturer

Senior Lecturer

Predictive Analytics, Smart Cities, Data Science, Machine Learning, Big Data & AI

Department of Engineering & Computing , School Of Architecture, Computing And Engineering

Dr Azhar Mahmood is a Senior Lecturer in the Department of Computing and Digital Technologies. He holds a PhD in Computer Science from Huazhong University of Science and Technology. Prior to his current position, Dr Mahmood served as an Associate Professor at CUST and SZABIST in Pakistan and as an Assistant Professor at NCU University, China. 

Qualifications

  • Doctor of Philosophy in Computer Applied Technology, Huazhong University of Science and Technology, P.R China
  • MS Software Engineering, Shaheed Zulfikar Ali Bhutto Institute of Science & Technology (SZABIST), Islamabad, Pakistan
  • MSc Computer Science, Sir Syed University of Engineering and Technology (SSUET) Karachi, Pakistan

Areas Of Interest

  • Data Mining
  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Decision Support Systems
  • Big Data Analytics
Dr Azhar Mahmood

OVERVIEW

Dr Mahmood's research focuses on Artificial Intelligence (AI), including Deep Learning, Data Mining, Machine Learning, and Natural Language Processing. He explores the application of these techniques in various fields, particularly Predictive Analytics in Healthcare and Smart Cities & IoT. He has authored over 35 publications in prestigious journals and successfully supervised four PhD dissertations, and several postgraduate and undergraduate theses/projects. 

Dr Mahmood has a proven track record of successful R&D projects in collaboration with international universities and organizations like Xiaomi (China), IBM & NIH (USA), SAP (Germany), and NUS (Singapore). His impactful research has garnered recognition at national and international levels, including winning R&D grants for his work on intelligent decision support systems in healthcare and wellbeing.

RESEARCH AND IMPACT

Research grants: 

  1. Co-PI: Predictive Analytics Lab, National Center of Big Data and Cloud Computing, Pakistan. Awarded grant of 81 Million PKR under national centres of research and innovation in emerging areas of science and technology 2018-2021.
  2. PI: Development of health diagnostics and predictive tools, National Institute of Health (NIH) USA, awarded a grant for prediction & diagnosis of infectious diseases 2021-2023. 
  3. PI: Development of Breast Cancer Multi-Stage Prediction Model, Awarded grant of 30k CNY under the program of Shanghai Cancer Research China, 2019-2021. 
  4. Co-PI: Research for Mortality Prediction of ICU Patients based on Intelligent Computing, awarded a grant of 100k CNY, Science and Technology Department of Jiangxi Province, Grant No: 20132BDH80017. 

PhD supervision:

  1. Sajjad Haider, Research Topic: Linguistic Rules to Identify Feature Words Related to Twitter Eyewitness Messages for Disaster Events - LR-TED (2020-2023) 
  2. Jibran Mir, Research Topic: A Novel Fine-Grained Sentiment Exploration Approach for Movie Reviews (2016-2020) 
  3. Farhan Sabir Ujager, Research Topic: A Context-Aware Wellness Determination Model (CAWDM) for Elderly People living in Smart Homes (2015-2019)

PUBLICATIONS

Peer-Reviewed Journals

  1. S. Nisa, A. Mahmood, et al., “HIV/AIDS predictive model using random forest based on socio-demographical, biological and behavioural data”, Egyptian Informatics Journal, Vol 24, No 1, Page 107-115, March 2023. (ISI Indexed, IF 4.19). 
  2. Z. Ali, A. Mahmood, et al., “A Generic Internet of Things (IoT) Middleware for Smart City Applications”, Sustainability Journal vol 15 no 1, page 743, Jan 2023. (ISI Indexed, IF 3.88). 
  3. S. Haider, A. Mahmood, et al., “Automatic Classification of Eyewitness Messages for Disaster Events Using Linguistic Rules and ML/AI Approaches”, Applied Sciences Journal vol 12 no 19, page 9953, Oct 2022. (ISI Indexed, IF 2.83). 
  4. S. Inam, A. Mahmood, et al., “Multisource data integration and comparative analysis of machine learning models for on-street parking prediction”, Sustainability Journal vol 14 no 12, page 7317, June 2022. (ISI Indexed, IF 3.88). 
  5. F. Ujager, A. Mahmood, et al., “A Hierarchical Energy Conservation Framework (HECF) of Wireless Sensor Networks by Temporal Association Rule Mining for Smart Buildings”, Egyptian Informatics Journal vol 23, no 1, page 137-147, March 2022. (ISI Indexed, IF 4.19). 
  6. J. Mir, A. Mahmood, S. Khatoon, “Multi-Level Knowledge Engineering Approach for Mapping Implicit Aspects to Explicit Aspects” Computers, Materials and Continua Journal, vol 70, no 2, page 3491-3509. January 2022. (ISI Indexed, IF 3.89). 
  7. S. Qazi, M. Usman, A. Mahmood, “A data-driven framework for introducing predictive analytics into expanded program on immunization in Pakistan”, Wiener klinische Wochenschrift, The Central European Journal of Medicine, Sep 2021, (ISI Indexed IF 2.27) 
  8. S. Qazi, M. Usman, A. Mahmood et al., Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI), “Computers, Materials & Continua Journal, Vol.66, No.1, pages.589-602, January 2021 (ISI Indexed, IF 3.89). 
  9. J. Mir, A. Mahmood, “Movie Aspects Identification Model for Aspect Based Sentiment Analysis”, Information Technology and Control Journal, Vol 49, No 4 December 2020. (ISI Indexed, IF 0.90) 
  10. M. Asad, A. Mahmood, M. Usman, “A Machine Learning-based Framework for Predicting Treatment Failure in Tuberculosis: A Case Study of Six Countries”, Tuberculosis Journal, vol. 123, Article 101944, June 2020(ISI Indexed IF 2.97). 
  11. M. Islam, M. Usman, A. Mahmood et al., “Predictive Analytics Framework for Accurate Estimation of Child Mortality Rates for Internet of Things Enabled Smart Healthcare Systems, “International Journal of Distributed Sensor Networks”, Vol: 16 No: 5, (ISI Indexed, IF 1.93). 
  12. F. Ujager, A. Mahmood, “Wellness Determination of Elderlies using Spatio-temporal Correlation Analysis of Daily Activities’, Journal of Ambient Intelligence and Smart Environments, vol. 11, no. 6, pp.515-526, Nov 2019. (ISI Indexed, IF 2.75). 
  13. F. Ujager, A. Mahmood et al., “A Context-Aware Accurate Wellness Determination (CAAWD) Model for Elderly People Using Lazy Associative Classification”, Sensors Journal Vol. 19, Pages 1613 April 2019. (ISI Indexed, IF 3.84). 
  14. N. Khan, A. Mahmood, A Distinctive Approach to Obtain Higher Page Rank through Search Engine Optimization, “SADHANA - Academy Proceedings in Engineering Sciences” March 2018. (ISI Indexed, IF 1.21). 
  15. J. Mir, A. Mahmood, S.Khatoon, Aspect-based Classification Model for Social Reviews, “Engineering Technology and Applied Science Research” Vol 7, No 6 December 2017, (ISI Indexed). 
  16. M Imran, A. Mahmood, S. Khatoon, “An Energy Efficient Model for WSN’s Monitoring Applications”, International Journal of Computer Science and Information Security Nov 2016): 363-373, (ISI Indexed). 
  17. F. Ujager, A. Mahmood et al, Evaluation of Wellness Detection Techniques using Complex Activities Association for Smart Home Ambient, “International Journal of Advanced Computer Science and Applications” Vol7 No. (8): September 2016, (ISI Indexed). 
  18. M. Khalifa, S. Khatoon, A. Mahmood et al, Factors Influencing Patients " Attitudes to Exchange Electronic Health Information in Saudi Arabia: An Exploratory Study, “International Journal of Advanced Computer Science and Applications” Vol7 No. (8) September 2016, (ISI Indexed). 
  19. Xu. Jianfeng, L. Yu, A. Mahmood et al, “WSN Missing Data Imputing Based on Multiple Time Granularity”, International Journal of Future Generation Communication and Networking, Vol. 9, No. 6 (2016), (ISI Indexed). 
  20. M.A. Mehmood, A. Mahmood, M.N.A Khan et al. “A Scenario-Based Distributed Testing Model for Software Applications”, International Journal of Advanced and Applied Sciences, Vol. 3, No10, October 2016, Page: 64-71, (ISI Indexed). 
  21. J. Xu, Y. Zhang, A. Mahmood et al., “Data Mining on ICU Mortality Prediction using Early Temporal Data”, International Journal of Information Technology and Decision Making, December 2016, (ISI Indexed IF 3.50). 
  22. M. Imran, R. Hashim, A. Irtaz, A. Mahmood, U. Abdullah. Class Wise Image Retrieval Through Scalable Color Descriptor and Edge Histogram Descriptor, “International Journal of Advanced and Applied Sciences” Volume 3, Issue 12, December 2016, Page: 32-36, (ISI Indexed). 
  23. R. Anum, M. Imran, R. Hahsim, A. Mahmood, S. Majeed. A Hybrid Particle Swarm Optimization (PSO) with Chi-Square and Stable Mutation Jump Strategy, “International Journal of Advanced and Applied Sciences” Volume 3, Issue 12 December 2016, Page: 49-54, (ISI Indexed). 
  24. A. Mahmood, K. Shi, S. Khatoon et al., “Data mining techniques for wireless sensor networks: A survey,” International Journal of Distributed Sensor Networks, 2013, (ISI Indexed, IF 1.93). 
  25. S. Khatoon, G. Li, and A. Mahmood, “Comparison and evaluation of source code mining tools and techniques: A qualitative approach,” Intelligent Data Analysis, vol. 17, no. 3, pp. 459-484, 201, March 2013 (ISI Indexed IF 1.32). 
  26. J. Xu, Li. Yu, A. Mahmood et al., “A Quotient Space Based Clustering Protocol for WSNs,” Information Technology Journal, vol. 13, no. 15, pp. 2442, 2014(Scopus, EI) 
  27. J. Xu, Y. Zhang, A. Mahmood et al., “A Hybrid Framework for ICU Mortality Prediction,” Journal of Software Engineering, vol. 8, no. 4, pp. 361-374, April 2014, (Scopus, EI) 
  28. A. Mahmood, K. Shi, and S. Khatoon, “An Efficient Distributed Data Extraction Method for Mining Sensor Networks Data,” International Journal of Computer Science Issues, vol. 10, no. 1, Jun 2013. (Scopus, EI) 
  29. A. Mahmood, and S. Khatoon, “An Approach to Generate Test Goals from Use Case Scenarios,” Information Technology Journal, vol. 12, no. 8, pp. 1600, 2013. (Scopus, EI) 
  30. S. Khatoon, A. Mahmood, and G. Li, “A Novel Integrated Framework to Increase Software Quality by Mining Source Code,” Journal of Software Engineering vol. 7, no. 3, pp. 86-105, March 2013. (Scopus, EI) 
  31. A. Mahmood, K. Shi, and S. Khatoon, “Mining data generated by sensor networks: a survey,” Information Technology Journal, vol. 11, no. 11, pp. 1534, 2012. (Scopus, EI) 32. S. Khatoon, and A. Mahmood, “Methodology for mapping business process into execution language,” International Journal of Engineering Science and Technology (IJEST), vol. 3, no. 1, 2011.

Conferences

  1. A. Mahmood, K. Shi, and S. Khatoon, “Controlling in-patient environment by mining sensor data,” in 10th International Conference, Fuzzy Systems and Knowledge Discovery (FSKD), Shenyang, 2013, pp. 674-679. (Scopus, EI).
  2. S. Khatoon, A. Mahmood, and G. Li, “An evaluation of source code mining techniques,” in 8th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Shanghai, 2011, pp. 1929-1933.(Scopus, EI).

MODULES

  • CN7000 MSc Computer Science Dissertations Supervision
  • CN6000 Project Supervision
  • CN5009/CN6007 2324 (T2) Mental Wealth
  • DS7010 MSc Data Science Dissertation Supervision

TEACHING

BSc (Hons) Computer Science

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MSc Data Science

Look at data across a wide range of subjects, including finance, crime, the environment, housing, education, demographics and social media.

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MSc Computer Science

Develop your knowledge and skills within the cutting-edge areas of computer science, gaining advanced theoretical knowledge and practical skills related to emerging technologies.

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