Furqan Alam,
researcher & teacher.
Failures are the first step towards success — so these days, I'm busy trying hard to fail.
An introduction.
Dr. Furqan Alam is an Assistant Professor at the Faculty of Computing and Information Technology, Sohar University, Oman. He is an academic, researcher, and technology professional with strong expertise in Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Computer Vision, Internet of Things, Smart Systems, and Generative AI.
Dr. Furqan completed both his M.Sc. and Ph.D. in Computer Science from King Abdulaziz University, Saudi Arabia, on awarded scholarship positions, reflecting his strong academic merit and research potential. During his academic and research journey, he had the opportunity to work with leading international researchers, including Prof. George N. Rouskas from North Carolina State University, USA, Prof. Rashid Mehmood, and Prof. Iyad Katib. He has also contributed to several internationally funded research projects, including projects supported by the National Science Foundation, USA.
Dr. Furqan has published widely in indexed international journals and conferences, with strong citation visibility across Google Scholar and ResearchGate. His research focuses on applying AI and machine learning to solve real-world problems in areas such as smart healthcare, medical image analysis, autonomous systems, smart cities, IoT, e-learning, human activity recognition, and sustainable technologies. His academic profile reflects a balance of high-quality research, practical innovation, and industry-relevant problem solving.
In addition to research and teaching, Dr. Furqan is actively involved in academic supervision, scholarly review, and editorial activities. He has supervised and guided multiple master's students in AI, Data Science, Machine Learning, image analysis, autonomous driving, smart infrastructure, healthcare systems, e-learning, IoT, and networking. He is also co-supervising a Ph.D. student in the area of advanced AI applications in healthcare. As part of his scholarly service, he serves as a reviewer for several reputed indexed journals and publishers, including IEEE, Springer, MDPI, Frontiers, and other international platforms. He has also been invited to serve as a Guest Editor for a Q1 journal special issue on intelligent learning systems.
Before joining Sohar University, Dr. Furqan gained diverse academic and industry experience as a Technology Lead in Data Science in Singapore, Program Manager in Data Science, Assistant Professor, AI Consultant, SAP ABAP Technical Consultant, and Research Collaborator at the High-Performance Computing Center, King Abdulaziz University. This combination of academic, research, and industry experience allows him to connect theoretical computing concepts with practical implementation.
At Sohar University, Dr. Furqan actively contributes to teaching, research, innovation, and industry collaboration. Recently, he was one of the academic experts involved in Sohar University's collaboration with Al Jazeera Steel Products Company to develop a bilingual Health, Safety, Security, and Environment Management System, supporting digital transformation, industrial safety, and academia–industry engagement in Oman.
Dr. Furqan's teaching philosophy is centered on connecting classroom learning with real-world problem solving. He encourages students to think beyond textbooks, explore emerging technologies, build research skills, and understand how Artificial Intelligence and computing can create meaningful impact in industry, society, and future careers.
Academic background.
Acquire knowledge, be confident; degrees do not matter much, but education matters.
Latest news & events.
Sohar University & Al Jazeera Steel sign agreement to develop a bilingual HSSE Management System
Sohar University signed a strategic collaboration agreement with Al Jazeera Steel Products Company to develop a comprehensive, bilingual Health, Safety, Security & Environment (HSSE) Management System. Dr. Furqan Alam (Faculty of Computing & Information Technology) and Prof. Rakesh Belwal (Faculty of Business) were named as the Sohar University academic experts developing the system, which aims to streamline HSSE orientation and reduce training time and cost while strengthening academia–industry engagement in Oman.
Read the announcement →Guest Editor — Special Issue: “Advances in Intelligent Learning Systems”
Dr. Furqan Alam is serving as Guest Editor for a Special Issue of Future Internet (MDPI, Q1), titled “Advances in Intelligent Learning Systems.” The issue welcomes original research and reviews on AI-driven learning across education, healthcare, and industry — spanning generative AI, LLMs, NLP, computer vision, and multimodal, personalized learning systems. The call for papers is now open, with submissions accepted until 1 April 2027.
View the special issue →Research interests.
All publications.
Confidence-weighted semi-supervised learning for skin lesion segmentation using hybrid CNN–Transformer networks
A resource-efficient approach to fine-tuning a BERT-base model for sentiment analysis
A review of the applications, benefits, and challenges of generative AI for sustainable toxicology
Benchmarking robust AI for microrobot detection with ultrasound imaging
Multi-objective optimisation of injection moulding process for dashboard using genetic algorithm and Type-2 fuzzy neural network
High-fidelity learning-based motion cueing algorithm by bypassing worst-case scenario-based tuning technique
NeuroHAR: A neuroevolutionary method for human activity recognition (HAR) for health monitoring
Evolutionary converging functions (ECF) as a novel object detection method for satellite images
TAAWUN: A decision fusion and feature-specific road detection approach for connected autonomous vehicles
Machine learning-enabled Internet of Things (IoT): Data, applications, and industry perspective
IResponse: An AI and IoT-enabled framework for autonomous COVID-19 pandemic management
Comparison of decision trees and deep learning for object classification in autonomous driving
Tutorial: Data analytics for Internet of Things
UTiLearn: A personalised ubiquitous teaching and learning system for smart societies
Data fusion and IoT for smart ubiquitous environments: A survey
D2TFRS: An object recognition method for autonomous vehicles based on RGB and spatial values of pixels
Analysis of eight data mining algorithms for smarter Internet of Things (IoT)
Analysis of round-robin load-balancing algorithm with adaptive and predictive approaches
Spectrum assignment in rings with shortest-path routing: Complexity and approximation algorithms
Architecture and algorithm for data fusion of heterogeneous multi-source information in Internet of Things (IoT) paradigm
Spectrum management techniques for elastic optical networks: A survey
New networking era: Software defined networking
Spectrum management techniques for elastic optical networks
In the classroom.
Research supervision.
Alongside doctoral supervision, Dr. Furqan has supervised and guided over a dozen master's students to successful completion. Their projects span artificial intelligence, natural language processing (NLP), large language models (LLMs), generative AI, machine learning, and computer vision — bridging rigorous research with real-world application.