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Dr. Tahir Alyas

Associate Professor

Status: Active

Dr. Tahir Alyas

Dr. Tahir Alyas

Associate Professor

ResearchGate Google Scholar Scopus ORCID

Research Interests

Artificial Intelligence, Machine Learning. Deep Learning

Biography

Dr. Tahir Alyas is Director ORIC and Associate Professor of Computer Science at Lahore Garrison University, Pakistan. He holds a PhD in Computer Science and specializes in Artificial Intelligence, Blockchain, Cloud Computing, Cybersecurity, Federated Learning, and Digital Governance. He has published more than 55 research papers in high-impact international journals, including Scientific Reports, IEEE Access, Sensors, and Frontiers. Dr. Alyas has supervised numerous postgraduate research projects and secured several national and international research grants. He serves as a reviewer for leading journals published by IEEE, Springer Nature, MDPI, and Tech Science Press and is a Senior Member of IEEE. His current research focuses on Explainable AI, Large Language Models, Healthcare Informatics, Smart Cities, and Blockchain-enabled digital transformation.

Year-wise Citations

Citations grouped by publication year from OpenAlex.

OpenAlex

Research Impact

OpenAlex metrics connected to the researcher's ORCID iD. Last synced Jun 03, 2026 11:32 PM.

OpenAlex
Total Publications 73
Total Citations 1,373
h-index 23
i10-index 39

Recent Publications

73 publications - Page 6 of 8

OpenAlex
  1. N. Tabassum, T. Alyas, M. Hamid, M. Saleem, S. Malik, Z. Ali, and U. Farooq, "Semantic Analysis of Urdu English Tweets Empowered by Machine Learning,", Intelligent Automation & Soft Computing, 2021, doi: 10.32604/iasc.2021.018998.
    19
    Open Access
  2. M. I. Tariq, N. A. Mian, A. Sohail, T. Alyas, and R. Ahmad, "Evaluation of the Challenges in the Internet of Medical Things with Multicriteria Decision Making (AHP and TOPSIS) to Overcome Its Obstruction under Fuzzy Environment,", Mobile Information Systems, 2020, doi: 10.1155/2020/8815651.
    22
    Open Access
  3. S. Abbas, M. A. Khan, A. Athar, S. A. Shan, A. Saeed, and T. Alyas, "Enabling Smart City With Intelligent Congestion Control Using Hops With a Hybrid Computational Approach,", The Computer Journal, 2020, doi: 10.1093/comjnl/bxaa068.
    48
  4. M. A. Khan, M. Habib, S. Saqib, T. Alyas, K. M. Khan, M. A. A. Ghamdi, and S. H. Almotiri, "Analysis of the Smart Player’s Impact on the Success of a Team Empowered with Machine Learning,", Computers, materials & continua/Computers, materials & continua (Print), 2020, doi: 10.32604/cmc.2020.012542.
    10
    Open Access
  5. M. A. Ullah, M. A. Khan, S. Abbas, T. Alyas, M. A. Saleem, and A. Fatima, "Blind Channel and Data Estimation Using Fuzzy Logic Empowered Cognitive and Social Information-Based Particle Swarm Optimization (PSO),", International Journal of Computational Intelligence Systems, 2020, doi: 10.2991/ijcis.d.200323.002.
    11
    Open Access
  6. M. A. Khan, S. Saqib, T. Alyas, A. U. Rehman, Y. Saeed, A. Zeb, M. Zareei, and E. M. Mohamed, "Effective Demand Forecasting Model Using Business Intelligence Empowered With Machine Learning,", IEEE Access, 2020, doi: 10.1109/access.2020.3003790.
    117
    Open Access
  7. D. M. Vistro, M. A. Saleem, T. Alyas, and S. Saqib, "OBJECTS DETECTION TECHNIQUES FROM IMAGES A SYSTEMATIC COMPARATIVE STUDY,", Article, 2020, View source.
    0
  8. A. Nasir, T. Alyas, M. Asif, and M. N. Akhtar, "Reliability Management Framework and Recommender System for Hyper-converged Infrastructured Data Centers,", 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2020, doi: 10.1109/icomet48670.2020.9074136.
    9
  9. M. A. Khan, R. A. Naqvi, N. Malik, S. Saqib, T. Alyas, and D. Hussain, "Roman Urdu News Headline Classification Empowered With Machine Learning,", Computers, materials & continua/Computers, materials & continua (Print), 2020, doi: 10.32604/cmc.2020.011686.
    14
    Open Access
  10. A. Ahmad, T. A. Rana, N. A. Mian, M. W. Iqbal, A. Khalid, T. Alyas, and M. Tubishat, "TOP-Rank: A Novel Unsupervised Approach for Topic Prediction Using Keyphrase Extraction for Urdu Documents,", IEEE Access, 2020, doi: 10.1109/access.2020.3039548.
    13
    Open Access