Power-efficient and highly scalable parallel graph sampling using FPGAs. - Muhammad Usman Tariq; Umer I. Cheema; Fahad Saeed (ReConFig, 2017)

Parallel Sampling-Pipeline for Indefinite Stream of Heterogeneous Graphs using OpenCL for FPGAs. - Muhammad Usman Tariq; Fahad Saeed (IEEE BigData, 2018)

SafeCity: Toward Safe and Secured Data Management Design for IoT-Enabled Smart City Planning. - Hui Zhang 038; Muhammad Babar; Muhammad Usman Tariq; Mian Ahmad Jan; Varun G. Menon; Xingwang Li 001 (IEEE Access, 2020)

Human Proteome and Peptides. - Muhammad Usman Tariq (IEEE DataPort, 2020)

An Improved Framework for Modelling Data Warehouse Systems Using UML Profile. - Muhammad Babar; Akmal Saeed Khattak; Fahim Arif; Muhammad Usman Tariq (Int. Arab J. Inf. Technol., 2020)

Graph Theoretic Approach for the Analysis of Comprehensive Mass-Spectrometry (MS/MS) Data of Dissolved Organic Matter. - Muhammad Usman Tariq; Dennys Leyvay; Francisco Alberto Fernandez Limaz; Fahad Saeed (BIBM, 2021)

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey. - Muhammad Usman Tariq; Muhammad Haseeb; Mohammed Aledhari; Rehma Razzak; Reza M. Parizi; Fahad Saeed (IEEE Access, 2021)

BP Neural Network Combination Prediction for Big Data Enterprise Energy Management System. - Sen Xu; Ryan Alturki; Ateeq Ur Rehman 001; Muhammad Usman Tariq (Mob. Networks Appl., 2021)

Smart teledentistry healthcare architecture for medical big data analysis using IoT-enabled environment. - Muhammad Babar; Muhammad Usman Tariq; Mohammad Dahman Alshehri; Fasee Ullah; Muhammad Irfan Uddin (Sustain. Comput. Informatics Syst., 2022)

Pre-Trained Model-Based NFR Classification: Overcoming Limited Data Challenges. - Kiramat Rahman; Anwar Ghani; Abdulrahman Alzahrani; Muhammad Usman Tariq; Arif Ur Rahman (IEEE Access, 2023)

Multi-Input Deep Learning Approach for Breast Cancer Screening Using Thermal Infrared Imaging and Clinical Data. - Dennies Tsietso; Abid Yahya; Ravi Samikannu; Muhammad Usman Tariq; Muhammad Babar; Basit Qureshi; Anis Koubaa (IEEE Access, 2023)

Image Encryption Scheme Based on Orbital Shift Pixels Shuffling with ILM Chaotic System. - Wajid Ali; Congxu Zhu; Rabia Latif; Muhammad Asim 002; Muhammad Usman Tariq (Entropy, 2023)

An Optimized IoT-Enabled Big Data Analytics Architecture for Edge-Cloud Computing. - Muhammad Babar; Mian Ahmad Jan; Xiangjian He; Muhammad Usman Tariq; Spyridon Mastorakis; Ryan Alturki (IEEE Internet Things J., 2023)

A Deep Features Based Approach Using Modified ResNet50 and Gradient Boosting for Visual Sentiments Classification. - Muhammad Arslan; Muhammad Mubeen; Arslan Akram; Saadullah Farooq Abbasi; Muhammad Salman Ali; Muhammad Usman Tariq (MIPR, 2024)

Beyond the Illusion: Ensemble Learning for Effective Voice Deepfake Detection. - Ghulam Ali; Javed Rashid; Muhammad Rameez Ul Hussnain; Muhammad Usman Tariq; Anwar Ghani; Daehan Kwak (IEEE Access, 2024)

Accurate Wheat Yield Prediction Using Machine Learning and Climate-NDVI Data Fusion. - Muhammad Ashfaq; Imran Khan 004; Abdulrahman Alzahrani; Muhammad Usman Tariq; Humera Khan; Anwar Ghani (IEEE Access, 2024)

Compiling Recurrences over Dense and Sparse Arrays. - Shiv Sundram; Muhammad Usman Tariq; Fredrik Kjolstad (Proc. ACM Program. Lang., 2024)

A hybrid model for energy-efficient Green Internet of Things enabled intelligent transportation systems using federated learning. - Sarah Kaleem; Adnan Sohail; Muhammad Babar; Awais Ahmad 001; Muhammad Usman Tariq (Internet Things, 2024)

Real-Time Fake News Detection Using Big Data Analytics and Deep Neural Network. - Muhammad Babar; Awais Ahmad 001; Muhammad Usman Tariq; Sarah Kaleem (IEEE Trans. Comput. Soc. Syst., 2024)

SKALP: Secure key agreement and lightweight protocol for dew-assisted IoT enabled edge computing. - Saeed Ullah Jan; Anwar Ghani; Abdulrahman Alzahrani; Muhammad Usman Tariq; Fahad Algarni; Syed Husnain Abbas Naqvi (Trans. Emerg. Telecommun. Technol., 2024)

An Efficient and Hybrid Deep Learning-Driven Model to Enhance Security and Performance of Healthcare Internet of Things. - Muhammad Babar; Muhammad Usman Tariq; Basit Qureshi; Zabeeh Ullah; Fahim Arif; Zahid Khan (IEEE Access, 2025)

Artificial intelligence driven demand forecasting: an application to the electricity market. - Marco Repetto; Cinzia Colapinto; Muhammad Usman Tariq (Ann. Oper. Res., 2025)