Publications

See my research profile at the following links.

 Dr. Farrukh's Profile at ResearchGate
                                                
                                           

Some of my publications... (for latest list of publications, please click the links given above)


 

Book Chapters

  1. Norah Alsaeed, Farrukh Nadeem, AI-enabled IoMT: transforming healthcare in smart hospitals, Blockchain and Digital Twin for Smart Hospitals, 459-496, 2025.
  2. T. Fahringer, R. Prodan, R.Duan, J. Hofer, F. Nadeem, F. Nerieri, S. Podlipnig, J. Qin, M. Siddiqui, H.-L. Truong, A. Villazon, M. Wieczorek, ASKALON: A Development and Grid Computing Environment for Scientific Workflows, in Workflows for eScience, Scientific Workflows for Grids, Springer Verlag, ISBN: 978-1-84628-519-6.
  3. Radu Prodan, Farrukh Nadeem, Thomas Fahringer. Benchmarking Grid applications for performance and scalability predictions. In Handbook of Research on Scalable Computing Technologies, pages 89-121, IGI Global, 2009.
  4. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Vincent Keller. An Evaluation of Availability Comparison and Prediction for Optimized Resource Selection in the Grid, In From Grids to Service and Pervasive Computing, Springer US, 2008, pages 63-76, ISBN: 978-0-387-09455-7.
  5. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Alexandru Iosup. A Framework For Resource Availability Characterization And Online Prediction In The Grids. In book “ Grid Computing: Achievements and Prospects”, Springer New York, NY, 2008, Pages 209-224, eBook ISBN: 978-0-387-09457-1. (selected among the best papers)
  6. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Alexandru Iosup. Benchmarking Grid Applications. In book: Grid Middleware and Services, Springer New York, 2008. doi: 10.1007/978-0-387-78446-5, eBook ISBN: 978-0-387-78446-5.
  7. Radu Prodan, Thomas Fahringer, Farrukh Nadeem, Marek Wieczorek. Real-World Workflow Support in the ASKALON Grid Environment. In book: Grid Middleware and Services, Springer New York, 2008. doi: 10.1007/978-0-387-78446-5, eBook ISBN: 978-0-387-78446-5.
  8. Farrukh Nadeem, Radu Prodan, and Thomas Fahringer. Optimizing performance of automatic training phase for application performance prediction in the Grid. In High Performance Computing and Communications (Lecture Notes in Computer Science), Volume 4782/2007, 309-321. Springer, September 2007.

Journal Publications

9.     Alanoud Alotaibi, Farrukh Nadeem, An Unsupervised Integrated Framework for Arabic Aspect-Based Sentiment Analysis and Abstractive Text Summarization of Traffic Services Using Transformer Models, Smart Cities 8 (2), 62, 2025. (IF=6.4, Top 10%; CiteScore: 8.5, Q1 journal).

10.  Mashail Alsolamy, Farrukh Nadeem, et. al. Automated Detection, Localization, and Severity Assessment of Proximal Dental Caries from Bitewing Radiographs Using Deep Learning, Diagnostics 15 (7), 899, 2025. (IF=3.0, CiteScore: 4.7, Q1 journal).

11.  Salha Al-Ahmari, Farrukh Nadeem, Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data, Diagnostics 15 (4), 501, 2025. (IF=3.0, CiteScore: 4.7, Q1 journal).

12.  Alanoud Alotaibi, Farrukh Nadeem and M. Hamdy, "Weakly Supervised Deep Learning for Arabic Tweet Sentiment Analysis on Education Reforms: Leveraging Pre-Trained Models and LLMs With Snorkel," in IEEE Access, vol. 13, pp. 30523-30542, 2025. (IF: 3.4, Scopus Q1 journal)

  1. Mashail Alsolamy, Farrukh Nadeem, et al., Automated detection and labeling of posterior teeth in dental bitewing X-rays using deep learning, Computers in Biology and Medicine 183, 109262, 2024. (IF=7.0, Top 6%; CiteScore: 11.7, Q1 journal).
  2. Alanoud Alotaibi and Farrukh Nadeem, Leveraging Social Media and Deep Learning for Sentiment Analysis for Smart Governance: A Case Study of Public Reactions to Educational Reforms in Saudi Arabia, Computers 13 (11), 280, 2024. (IF=2.6, CiteScore: 5.4, Q2 journal).

15.  Norah Alsaeed, Farrukh Nadeem. “A Scalable and Lightweight Group Authentication Framework for Internet of Medical Things Using Integrated Blockchain and Fog Computing”, Future Generation Computer Systems, Elsevier, Volume 151, Pages 162-181, 2024. (IF: 7.5, Top 10%; Q1 journal).

  1. Alharbi, Eman T., Asma Cherif, and Farrukh Nadeem, Adaptive Smart eHealth Framework for Personalized Asthma Attack Prediction and Safe Route Recommendation, Smart Cities, 6(5), 2910-2931, 2023. (IF=6.4, Top 10%; CiteScore: 8.5, Q1 journal).
  2. Farrukh Nadeem, “Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models based on Functional and Non-Functional Key Performance Indicators”, IEEE Access, vol. 10, pp. 63245-63257, 2022. (IF: 3.9, Scopus Q1 journal)
  3. Alharbi, Eman T., Farrukh Nadeem, and Asma Cherif. "Predictive models for personalized asthma attacks based on patient’s biosignals and environmental factors: a systematic review." BMC Medical Informatics and Decision Making, 21, no. 1, 1-13, 2022. (IF: 3.5, Scopus Q1 Journal).
  4. Norah Alsaeed, Farrukh Nadeem. “Authentication in the Internet of Medical Things: Taxonomy, Review, and Open Issues”, Applied Sciences. 2022; 12(15):7487. https://doi.org/10.3390/app12157487 (IF: 2.84, Q2 journal).
  5. Almutiri, Talal, and Farrukh Nadeem, "Markov Models Applications in Natural Language Processing: A Survey", I. J. Information Technology and Computer Science, 2(1),  (2022), 1-16.
  6. Alanoud Alotaibi, Farrukh Nadeem, “A Review of Applications of Linear Programming to Optimize Agricultural Solutions” in International Journal of Information Engineering and Electronic Business, Vol. 3, issue 2, p 11-21, 2021.
  7. Alqahtani, Norah, and Farrukh Nadeem, "Improving the Effectiveness of e-Learning Processes through Dynamic Programming: A Survey." International Journal of Advanced Computer Science and Applications, 12, no. 5, 2021. (CiteScore: 2.1, Q3 Journal).
  8. Farrukh Nadeem, “A Unified Framework for User-Preferred Multi-Level Ranking of Cloud Computing Services Based on Usability and Quality of Service Evaluation” in IEEE Access, 8, 180054-180066, 2020. (IF: 3.9, Scopus Q1 journal).
  9. Farrukh Nadeem, “Using Radial Basis Function Neural Network to Predict Dynamic Resource Availability in Heterogeneous Distributed Environments” in Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5619-5632, 2019. (IF=2.0, Scopus Q1 journal, top 19% journal).
  10. Farrukh Nadeem, D. Alghazzawi, A. Mashat, K. Faqeeh and A. Almalaise, "Using Machine Learning Ensemble Methods to Predict Execution Time of e-Science Workflows in Heterogeneous Distributed Systems," in IEEE Access, vol. 7, pp. 25138-25149, 2019. (IF=3.9, Scopus Q1 journal).
  11. Sultan Algarni, Mohammad Rafi Ikbal, Roobaea Alroobaea, Ahmed Ghiduk, Farrukh Nadeem, Performance Evaluation of Xen, KVM, and Proxmox Hypervisors, International Journal of Open Source Software and Processes (IJOSSP), Volume 9, Issue 2, 2018. (CiteScore: 1.9). 
  12. Farrukh Nadeem, D. Alghazzawi, Abdulfattah Mashat, K. Faqeeh and A. Almalaise, Modeling and predicting execution time of scientific workflows in the Grid using radial basis function neural network, Journal of Cluster Computing, Volume 20, Issue 3, pp 2805–2819, Springer, September 2017. (IF= 4.4, Q1 journal).
  13. Osama Islam, Ahmed Alfakeeh, Farrukh Nadeem, A Framework for Effective Big data Analytics for Decision Support Systems, International Journal of Computer Networks and Applications, Volume 4, Issue 5, September 2017. (Scopus CiteScore: 1.3).
  14. Manal Abumelha, Awatef Hashbal, Farrukh Nadeem, Naif Aljohani, Development of Infection Control Surveillance System for Intensive Care Unit: Data Requirements and Guidelines, International Journal of Intelligent Systems and Applications, 8(6): 19-26, 2016.
  15. Sahar S. Alqahtani, Sabah Alshahri, Ahood I. Almaleh, Naif Aljohani, Farrukh Nadeem, The Implementation of Clinical Decision Support System: A Case Study in Saudi Arabia, International Journal of Information Technology and Computer Science, 8(8): 23-30, 2016.
  16. Farrukh Nadeem, A Taxonomy of Data Management Models in Distributed and Grid Environments, International Journal of Information Technology and Computer Science, 8(3): 19-32, 2016.
  17. Farrukh Nadeem, Rizwan Qaiser, An Early Evaluation and Comparison of Three Private Cloud Computing Software Platforms, Journal of computer science and technology, Volume 30, issue 3, pages 639-654, Springer, DOI 10.1007/s11390-015-1550-1, 2015.  (IF=1.9, Scopus Q2 journal). 
  18. Farrukh Nadeem, Ranking Grid-sites based on their Reliability for Executing Jobs Successfully. International Journal of Computer Network and Information Security, Volume 7, issue 5, pages 9-15, 2015, DOI: 10.5815/ijcnis.2015.05.02, 2015. (CiteScore: 3.7, Q2 Journal).
  19. Farrukh Nadeem, Salma Mahgoub, Student-centered Role-based Case Study Model to Improve Learning in Decision Support Systems, International Journal of Modern Education and Computer Science, ISSN: 2075-0161, 2014, Volume 6, Issue 10, pages 16-22, DOI: 10.5815/ijmecs.2014.10.03, 2014. (IF: 0.13, CiteScore: 3.6, Q2 journal).
  20. Farrukh Nadeem, Thomas Fahringer, Optimizing execution time predictions of scientific workflow applications in the Grid through evolutionary programming. Future Generation Computer Systems, Elsevier, Volume 29, Issue 4, pages: 926-935, 2013. (IF: 7.5, Q1 journal, Top 10% journal). 

Conference Proceedings

  1. E Alharbi, A Cherif, Farrukh Nadeem, T Mirza, “Machine Learning Models for Early Prediction of Asthma Attacks Based on Bio-signals and Environmental Triggers”, IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA), 2022.
  2. Alsaeed, Norah, and Farrukh Nadeem. "A Framework for Blockchain and Fogging-based Efficient Authentication in Internet of Things." In 2022 2nd International Conference on Computing and Information Technology (ICCIT), pp. 409-417. IEEE, 2022.
  3. Eman Alharbi, Farrukh Nadeem, Asma Cherif, “Smart Healthcare Framework for Asthma Attack Prediction and Prevention” in fourth National Conference of Saudi Computers Colleges, Taif, Saudi Arabia, published by IEEE, 2021, pp. 1-6.
  4. Salha Al-Ahmari, Farrukh Nadeem, “Machine Learning-Based Predictive Model for Surgical Site Infections: A Framework”, in fourth National Conference of Saudi Computers Colleges, Taif, Saudi Arabia, published by IEEE, 2021, pp. 1-6.
  5. Mohammed Matuq Ashi, Muazzam Ahmed Siddiqui, Farrukh Nadeem, Pre-trained Word Embeddings for Arabic Aspect-Based Sentiment Analysis of Airline Tweets, Proceedings of the International Conference on Advanced Intelligent Systems and Informatics, 2018, Cairo, Egypt. Publisher Springer.
  6. Salma Elhag, Farrukh Nadeem, Interactive Case Based Learning in Teaching Decision Support Systems and Business Intelligence. In Proceedings of International Conference Interaccion 2012, October 3-5, 2012, Elche, Spain. publisher ACM, New York. 
  7. Farrukh Nadeem, Thomas Fahringer, Predicting the execution time of grid workflow applications through local learning. In Proceedings of IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis 2009 (Supercomputing 2009, SC|09), pages 1--12, Nov. 14-20, 2009, Portland, Oregon, publisher ACM, New York, NY, USA. IEEE Computer Society.
  8. Farrukh Nadeem, Thomas Fahringer, Using templates to predict execution time of scientific workflow applications in the grid. In Proceedings of 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid'09), Shanghai, China, May 18-21, 2009, IEEE Computer Society Press. 
  9. Rubing Duan, Farrukh Nadeem, Jie Wang, Radu Prodan, and Thomas Fahringer. A hybrid intelligent approach for performance modeling and prediction of workflow activities in Grids. In 9th International Symposium on Cluster Computing and the Grid. IEEE Computer Society, 2009. 
  10. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Characterizing, Modeling and Predicting Dynamic Resource Availability in a Large Scale Multi-Purpose Grid. In Proceedings of 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid'08), Lyon, France, May 19-22, 2008, (c) IEEE Computer Society Press.
  11. Erik Elmroth, Johan Tordsson, Thomas Fahringer, Farrukh Nadeem, Ralf Gruber, Vincent Keller, Three Complementary Performance Prediction Methods for Grid Applications, In Proceedings of CoreGRID Integration Workshop 2008, Hersonisson, Crete, Greece, April 2-4, 2008.
  12. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Soft Benchmarks-based Application Performance Prediction using a Minimum Training Set, 2nd IEEE International Conference on e-Science and Grid Computing (e-Science 2006), (C) IEEE Computer Society Press, December 2006, Amsterdam, The Netherlands.
  13. Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Reducing the complexity of Automatic Training Phase for Performance Prediction in the Grid, 2nd Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, Oct. 27.-29.2006, Mikulov, Czek Republic.
  14. Felix Schüller, Jun Qin, Farrukh Nadeem, Radu Prodan, Thomas Fahringer, Georg Mayr, Performance, Scalability and Quality of the Meteorological Grid Workflow MeteoAG, 2nd Austrian Grid Symposium, University Innsbruck, September 21 - 23, 2006. Published by OCG Verlag.
  15. Muhammad Ali, Michael Welzl, Awais Adnan, Farrukh Nadeem, Using the ns-2 network simulator for evaluating network on chips, In Proceedings of IEEE International Conference on Emerging Technologies (IEEE ICET 2006), Peshawar, Pakistan, 13-14 November 2006.
  16. Farrukh Nadeem, Muhammad Murtaza Yousaf, Muhammad Ali,  Grid Performance Prediction: Requirements, Framework, and Models, In Proceedings of IEEE International Conference on Emerging Technologies (IEEE ICET 2006), Peshawar, Pakistan, 13-14 November 2006.
 


Last Update
6/4/2025 1:55:53 AM