Basharat Hussain

About

Dr. Basharat Hussain (ORCID: 0000-0001-7492-5725) is an Assistant Professor in the Department of Computer Science at FAST University (NUCES), Islamabad. He holds a Ph.D. in Computer Science from COMSATS University Islamabad and an M.S. in Computer Science with distinction from the International Islamic University, Islamabad.

Dr. Hussain’s research focuses on deep learning, federated learning, and large language models (LLMs), with applications in intelligent transportation systems and autonomous vehicles. His technical expertise includes Python, PyTorch, TensorFlow, Hugging Face, and cloud platforms like AWS and Azure. He is active in open-source communities and passionate about mentoring, interdisciplinary collaboration, and AI and software engineering innovation.

With over 25 years of experience in both academia and industry, Dr. Hussain has led product development for multinational corporations across Europe and the United States. He has held senior roles, including CTO, software architect, and technical lead at various organizations. His work spans real-time systems, scalable machine learning applications, and cloud-native software architecture. In addition to his research and teaching, he brings hands-on expertise in C++, C#, ASP.NET, Java, Matlab, and software architecture for robust, enterprise-grade solutions. He is also the Director of IT at Royal Brackets Technologies SMC Ltd.

Dr. Hussain remains committed to advancing impactful research, excellence in teaching, and industry innovation in computer science

Employment

• National University of Computer and Emerging Sciences Assistant Professor
  2024 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• Integrating Retrieval-Augmented Generation with Large Language Model for Robust and Explainable AI Text Detection
  Knowledge 2026 DOI: 10.3390/knowledge6030022
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• Pose and Illumination Invariant Face Recognition in Video via Motion Analysis and Texture Feature Optimization
  IET Image Processing 2025 DOI: 10.1049/ipr2.70211
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• Optimizing Content Cache With Vehicular Edge Computing: A Deep Federated Learning-Based Novel Predictive Study
  Azan Ali Khan, Basharat Hussain, Muhammad Islam Satti +2 more
  IEEE Transactions on Consumer Electronics 2025 DOI: 10.1109/TCE.2025.3571029
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• Optimizing Urban Traffic Incident Prediction With Vertical Federated Learning: A Feature Selection Based Approach
  IEEE Transactions on Network Science and Engineering 2025 DOI: 10.1109/TNSE.2024.3487268
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• A Novel Graph Convolutional Gated Recurrent Unit Framework for Network-based Traffic Prediction
  IEEE Access 2023 DOI: 10.1109/access.2023.3333938
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• Intelligent Traffic Flow Prediction Using Optimized GRU Model
  IEEE Access 2021 DOI: 10.1109/access.2021.3097141
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