Soft Benchmarks-Based Application Performance Prediction Using a Minimum Training Set. - Farrukh Nadeem; Muhammad Murtaza Yousaf; Radu Prodan; Thomas Fahringer (e-Science, 2006)

ASKALON: A Development and Grid Computing Environment for Scientific Workflows. - Thomas Fahringer; Radu Prodan; Rubing Duan; Jürgen Hofer; Farrukh Nadeem; Francesco Nerieri; Stefan Podlipnig; Jun Qin; Mumtaz Siddiqui; Hong Linh Truong 001; Alex Villazón; Marek Wieczorek (Workflows for e-Science, Scientific Workflows for Grids, 2007)

Optimizing Performance of Automatic Training Phase for Application Performance Prediction in the Grid. - Farrukh Nadeem; Radu Prodan; Thomas Fahringer (HPCC, 2007)

Characterizing, Modeling and Predicting Dynamic Resource Availability in a Large Scale Multi-purpose Grid. - Farrukh Nadeem; Radu Prodan; Thomas Fahringer (CCGRID, 2008)

A Framework For Resource Availability Characterization And Online Prediction In The Grids. - Farrukh Nadeem; Radu Prodan; Thomas Fahringer; Alexandru Iosup (CoreGRID Integration Workshop, 2008)

A Hybrid Intelligent Method for Performance Modeling and Prediction of Workflow Activities in Grids. - Rubing Duan; Farrukh Nadeem; Jie Wang; Yun Zhang; Radu Prodan; Thomas Fahringer (CCGRID, 2009)

Using Templates to Predict Execution Time of Scientific Workflow Applications in the Grid. - Farrukh Nadeem; Thomas Fahringer (CCGRID, 2009)

Predicting the execution time of grid workflow applications through local learning. - Farrukh Nadeem; Thomas Fahringer (SC, 2009)

Interactive case based learning in teaching decision support systems and business intelligence. - Salma Mahgoub; Farrukh Nadeem (Interacción, 2012)

Optimizing execution time predictions of scientific workflow applications in the Grid through evolutionary programming. - Farrukh Nadeem; Thomas Fahringer (Future Gener. Comput. Syst., 2013)

An Early Evaluation and Comparison of Three Private Cloud Computing Software Platforms. - Farrukh Nadeem; Rizwan Qaiser (J. Comput. Sci. Technol., 2015)

Modeling and predicting execution time of scientific workflows in the Grid using radial basis function neural network. - Farrukh Nadeem; Daniyal M. Alghazzawi; Abdulfattah S. Mashat; Khalid Fakeeh; Abdullah Al-Malaise Al-Ghamdi; Hani Hagras (Clust. Comput., 2017)

Pre-trained Word Embeddings for Arabic Aspect-Based Sentiment Analysis of Airline Tweets. - Mohammed Matuq Ashi; Muazzam Ahmed Siddiqui; Farrukh Nadeem (AISI, 2018)

Knowledge Based e-Health Surveillance System for Predicting Hospital Acquired Infections. - Amin Y. Noaman; Nabeela Al-Abdullah; Arwa A. Jamjoom; Abdul Hamid M. Ragab; Farrukh Nadeem; Anser G. Ali (COMPSAC (2), 2018)

Performance Evaluation of Xen, KVM, and Proxmox Hypervisors. - Sultan Abdullah Algarni; Mohammad Rafi Ikbal; Roobaea Alroobaea; Ahmed S. Ghiduk; Farrukh Nadeem (Int. J. Open Source Softw. Process., 2018)

Using Machine Learning Ensemble Methods to Predict Execution Time of e-Science Workflows in Heterogeneous Distributed Systems. - Farrukh Nadeem; Daniyal M. Alghazzawi; Abdulfattah S. Mashat; Khalid Faqeeh; Abdullah Al-Malaise Al-Ghamdi (IEEE Access, 2019)

Using radial basis function neural network to predict dynamic resource availability in heterogeneous distributed environments. - Farrukh Nadeem (J. Intell. Fuzzy Syst., 2019)

A Unified Framework for User-Preferred Multi-Level Ranking of Cloud Computing Services Based on Usability and Quality of Service Evaluation. - Farrukh Nadeem (IEEE Access, 2020)

Predicting and reducing "hospital-acquired infections" using a knowledge-based e-surveillance system. - Amin Y. Noaman; Abdul Hamid M. Ragab; Nabeela Al-Abdullah; Arwa A. Jamjoom; Farrukh Nadeem; Anser G. Ali (Expert Syst. J. Knowl. Eng., 2020)

Predictive models for personalized asthma attacks based on patient's biosignals and environmental factors: a systematic review. - Eman T. Alharbi; Farrukh Nadeem; Asma Cherif 001 (BMC Medical Informatics Decis. Mak., 2021)

Machine Learning Models for Early Prediction of Asthma Attacks Based on Bio-signals and Environmental Triggers. - Eman T. Alharbi; Asma Cherif 001; Farrukh Nadeem; Tariq Mirza (AICCSA, 2022)

Evaluating and Ranking Cloud IaaS, PaaS and SaaS Models Based on Functional and Non-Functional Key Performance Indicators. - Farrukh Nadeem (IEEE Access, 2022)

Automated detection and labeling of posterior teeth in dental bitewing X-rays using deep learning. - Mashail Alsolamy; Farrukh Nadeem; Amr Ahmed Azhari; Wafa Alsolami; Walaa Magdy Ahmed (Comput. Biol. Medicine, 2024)

Leveraging Social Media and Deep Learning for Sentiment Analysis for Smart Governance: A Case Study of Public Reactions to Educational Reforms in Saudi Arabia. - Alanoud Alotaibi; Farrukh Nadeem (Comput., 2024)

A scalable and lightweight group authentication framework for Internet of Medical Things using integrated blockchain and fog computing. - Norah Alsaeed; Farrukh Nadeem; Faisal Albalwy (Future Gener. Comput. Syst., 2024)

Weakly Supervised Deep Learning for Arabic Tweet Sentiment Analysis on Education Reforms: Leveraging Pre-Trained Models and LLMs With Snorkel. - Alanoud Alotaibi; Farrukh Nadeem; Mohamed Hamdy El-Eliemy (IEEE Access, 2025)