About

Dr Mian Usman Sattar is a leading academic and interdisciplinary researcher whose expertise spans Artificial Intelligence (AI), Business Intelligence, and Human-Computer Interaction (HCI). His research is grounded in a leadership-focused, impact-driven ethos that integrates theoretical advancements with real-world applications across healthcare, education, and industry.

With a portfolio of over 40 peer-reviewed publications and active contributions to nationally and internationally funded projects, Dr Sattar is committed to advancing intelligent, user-centred technologies that address complex societal challenges. He plays a pivotal role in grant acquisition, research coordination, and the development of high-impact outputs that support the UK’s strategic position in AI and digital innovation. Dr Sattar is internationally recognised for his academic contributions, serving on the editorial and advisory boards of several high-impact journals and as a peer reviewer for numerous leading publications. He is actively engaged in the global research community, having chaired sessions and delivered technical expertise at prestigious international conferences, including IEEE CMT, ISBI, CogMI, ACM, and SKIMA.

At the institutional level, Dr Sattar demonstrates sustained academic leadership through curriculum enhancement, digital pedagogy, and research mentorship. He has led the redesign of multiple modules to align with student feedback, industry needs, and contemporary learning approaches. His collaborative and inclusive approach to teaching and supervision reflects a commitment to student empowerment and lifelong learning. Dr Sattar also contributes significantly to university-wide initiatives, including research strategy panels, access and participation groups, and outreach events. His ability to lead interdisciplinary teams and deliver strategically aligned outcomes underscores his vision, adaptability, and dedication to academic excellence.

I am an active member of Data Science Research Centre.

Teaching responsibilities

My teaching responsibilities include the following courses:

• Processing Big Data
• Information Visualisation
• Scripting and Web Technologies
• IT Product Design
• Analytics, Ethics, Trust and Governance
• Software Engineering

In my previous roles, I have undertaken modules that include:

• Data Science
• Systems Analysis and Design
• Introduction to Programming
• Database Management
• Website Design and Development

In addition to the above modules, I could teach courses on Machine Learning, Data Analytics, AI and Applications, and other Computing-related modules.

Professional interests

My research interests lie at the intersection of Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Immersive Technologies, with a strong focus on applying these cutting-edge tools to solve complex, real-world problems across diversified domains.

I am particularly driven by the transformative potential of AI in both business and medical sciences, two fields where intelligent systems can make a measurable impact on human lives and organizational performance. In the business domain, my work explores e-commerce and targeted marketing, leveraging data-driven models and natural language processing (NLP) to understand consumer behaviour, personalize user experiences, and optimize decision-making processes. In parallel, my contributions to health informatics centre on developing AI-powered solutions for medical image classification, early disease detection, and clinical decision support systems, helping healthcare professionals deliver more accurate and timely interventions.

I am also deeply engaged with immersive technologies such as Virtual and Augmented Reality, investigating their integration with AI to create intuitive, user-centred environments for education, therapy, and cognitive assessment. By bridging technical innovation with domain-specific needs, my research aims to create scalable, ethical, and human-centric solutions that not only advance academic understanding but also bring tangible value to industry and society.

Research interests

My interdisciplinary research spans Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Immersive Technologies, with a strong emphasis on their integration to address complex challenges in both medical science and diversified business domains.

In healthcare, I explore the application of AI for early diagnosis, predictive analytics, and medical imaging classification, while employing HCI principles to design intuitive systems that support clinicians and enhance patient engagement. Immersive technologies such as Virtual and Augmented Reality further enrich this space by enabling interactive cognitive assessments, therapeutic interventions, and training environments tailored to individual needs. Simultaneously, in the business sphere, I investigate how AI and HCI can optimize customer experience, drive intelligent automation, and support data-driven strategies in areas like e-commerce, targeted marketing, and business intelligence.

This interdisciplinary approach aligns with the UK’s National AI Strategy, which emphasizes leveraging AI to strengthen the economy, improve healthcare outcomes, and position the UK as a global leader in trustworthy and responsible AI. By fusing these technological pillars, my work contributes to the creation of scalable, user-centric, and ethically grounded solutions that promote innovation, drive productivity, and deliver meaningful societal impact, reflecting the UK’s vision of AI that works for people, businesses, and the public good.

Qualifications

• PhD Informatics (Malaysia University of Science and Technology, Malaysia)
• MS IT Management (University of Sunderland, UK)
• MSc Computer Science (Government College University, Lahore, Pakistan)

Recent publications

• Usman Sattar, M., Dattana, V., Hasan, R., Mahmood, S., Wazir Khan, H., & Hussain, S. (2025). Enhancing Supply Chain Management: A Comparative Study of Machine Learning Techniques with Cost–Accuracy and ESG-Based Evaluation for Forecasting and Risk Mitigation. Sustainability 2025, Vol. 17, Page 5772, 17(13), 5772. https://doi.org/10.3390/SU17135772
• Sattar, M. U., Ufeli, C. P., Hasan, R., & Mahmood, S. (2025). Enhancing Customer Segmentation Through Factor Analysis of Mixed Data (FAMD)-Based Approach Using K-Means and Hierarchical Clustering Algorithms. Information, 16(6), 441. https://doi.org/10.3390/INFO16060441
• Usman Sattar, M., Wazir Khan, H., Ghaffar, A., Murad, H., & Raza, S. (2025). Exploring the Impact of Augmented Reality on Medical Students’ Intrinsic Motivation: A Three-Dimensional Analysis. Journal of Management & Social Science, 2(2), 257–276. https://doi.org/10.63075/DT4F4H66
• Abdi, H., Sattar, M. U., Hasan, R., Dattana, V., & Mahmood, S. (2025). Stroke Detection in Brain CT Images Using Convolutional Neural Networks: Model Development, Optimization and Interpretability. Information 2025, Vol. 16, Page 345, 16(5), 345. https://doi.org/10.3390/INFO16050345
• Gamawelagedara, M. P. B., Sattar, M. U., & Hasan, R. (2025). Mitigating fuel station drive-offs using AI: YOLOv8 OCR and MOT History API for detecting fake and altered plates. Computers, Materials and Continua, 0(0), 1–10. https://doi.org/10.32604/CMC.2025.062826
• Sattar, M. U., Khan, H. W., Khan, H. W., Hassan, R., Hassan, R., & Hassan, A. (2024). A Human-Centered Design Framework for Intuitive Mobile AR in Medical Learning. UMT Education Review, 7(2), 94-122–194–122.
• Qureshi, Z., Nadeem, T., & Sattar, M. U. (2023). Using Analytics to Explore the Link Between Confidence and Delay in Task Completion Among Undergraduate Students. Journal of Applied Research and Multidisciplinary Studies (JARMS), 4(2), 2023.
• Ahmad, B., Sattar, M. U., Khan, H. W., Qureshi, Z., Hasan, R., Ahmad, A., & Azad, M. (2021). Intelligent Digital Twin to make Robot Learn the Assembly process through Deep Learning.
• Almadhor, A., Sattar, U., Al Hejaili, A., Ghulam Mohammad, U., Tariq, U., & Ben Chikha, H. (2022). An efficient computer vision-based approach for acute lymphoblastic leukemia prediction. Frontiers in Computational Neuroscience.
• Apsari, N. F., Megantoro, P., Sattar, M. U., Maseleno, A., & Tanane, O. (2020). Design of laboratory scale fluid level measurement device based on arduino. Journal of Robotics and Control (JRC), 1(5), 145–149.
• Ghafar, A., & Sattar, U. (2021). Convolutional Autoencoder for Image Denoising. UMT Artificial Intelligence Review, 1(2), 1–11. https://doi.org/10.32350/AIR.0102.01
• Ghaffar, A., Alanazi, S., Alruwaili, M., Sattar, M. U., Ali, W., Humayun, M., Siddiqui, S. Y., Ahmad, F., & Khan, M. A. (2021). Multi-stage intelligent smart lockdown using sir model to control covid 19. Intelligent Automation and Soft Computing, 28(2), 429–445. https://doi.org/10.32604/iasc.2021.014685
• Ghaffar, A., Sattar, M. U., Munir, M., & Qureshi, Z. (2022). Multi-objective fuzzy-based adaptive memetic algorithm with hyper-heuristics to solve university course timetabling problem. EAI Endorsed Transactions on Scalable Information Systems, 9(4), 1–16. https://doi.org/10.4108/eai.16-12-2021.172435
• Ghani, F., Sattar, U., Narmeen, M., Wazir Khan, H., & Mehmood, A. (2021). A Methodology for Glaucoma Disease Detection Using Deep Learning Techniques. International Journal Of Computing and Digital System, 1(1), 1–11. https://journal.uob.edu.bh/handle/123456789/4416
• Hasan, R., Palaniappan, S., Mahmood, S., Abbas, A., Sarker, K. U., & Sattar, M. U. (2020). Predicting Student Performance in Higher Educational Institutions Using Video Learning Analytics and Data Mining Techniques. Applied Sciences, 10(11), 3894. https://doi.org/10.3390/app10113894
• Hasan, R., Palaniappan, S., Mahmood, S., Naidu, V. R., Agarwal, A., Singh, B., Sarker, K. U., Abbas, A., & Sattar, M. U. (2020). A Review: Emerging Trends of Big Data in Higher Educational Institutions. In Lecture Notes in Networks and Systems (Vol. 106). Springer Singapore. https://doi.org/10.1007/978-981-15-2329-8_29
• Hasan, R., Palaniappan, S., Mahmood, S., Sarker, K. U., Sattar, M. U., Abbas, A., Naidu, V. R., & Rajegowda, P. M. (2021). eDify: Enhancing Teaching and Learning Process by Using Video Streaming Server. International Journal of Interactive Mobile Technologies, 15(11), 49–65. https://doi.org/10.3991/ijim.v15i11.20245
• Megantoro, P., Husnan, D. A., Sattar, M. U., Maseleno, A., & Tanane, O. (2020). Validation method for digital flow meter for fuel vendors. Journal of Robotics and Control (JRC), 1(2), 44–48. https://doi.org/10.18196/jrc.1210
• Narmeen, M., Sattar, M. U., Khan, H. W., Fatima, M., Azad, M.-D., & Ghani, F. (2022). Impact of Weather on COVID-19 in Metropolitan Cities of Pakistan: A Data-Driven Approach. International Journal of Computing and Digital Systems, 11(1), 905–915. https://doi.org/10.12785/ijcds/110174
• Nisar, H., Wajid, B., Shahid, S., Anwar, F., Wajid, I., Khatoon, A., Sattar, M. U., & Sadaf, S. (2021). Whole-genome sequencing as a first-tier diagnostic framework for rare genetic diseases. Experimental Biology and Medicine, 246(24), 2610–2617. https://doi.org/10.1177/15353702211040046
• Rizwan, M., & Sattar, M. U. (2019). 5G Radio Access Networks Based on Fog Computing : an Overview. Journal of Natural and Applied Sciences Pakistan, 1(May), 46–51.
• Sattar, M., Palaniappan, S., Lokman, A., Shah, N., Riaz, Z., & Khalid, U. (2019). User experience design in virtual reality medical training application. Journal of the Pakistan Medical Association, 71(7), 1. https://doi.org/10.5455/JPMA.22992
• Sattar, M. U., Imran, M., Khan, H. W., Ghaffar, A., & Mushtaq, H. (2022). Selecting a Better Classifier Using Machine Learning for COVID-19. International Journal of Computing and Digital Systems, 11(1), 955–962. https://doi.org/10.12785/ijcds/110178
• Sattar, M. U., Mubashar, A., Fareed, R., & Rizwan, M. (2021). Architectures, Security Issues, and Usage Scenarios of EC. UMT Artificial Intelligence Review, 1(1), 1–1. https://doi.org/10.32350/umtair.11.04
• Sattar, M. U., Palaniappan, S., Lokman, A., Hassan, A., Shah, N., & Riaz, Z. (2019). Effects of Virtual Reality training on medical students’ learning motivation and competency. Pakistan Journal of Medical Sciences, 35(3). https://doi.org/10.12669/pjms.35.3.44
• Sattar, M. U., Palaniappan, S., Lokman, A., Shah, N., Khalid, U., & Hasan, R. (2020). Motivating Medical Students Using Virtual Reality Based Education. International Journal of Emerging Technologies in Learning (IJET), 15(02), 160. https://doi.org/10.3991/ijet.v15i02.11394
• Sattar, M. U., & Sattar, B. (2012). Analyzing the Impact of Customer Satisfaction on Customer Loyalty: A Data-Driven Study in Pakistan’s Telecommunication Sector. Asian Journal of Business and Management, 4(3), 252–259.
• Wijaya, N. H., Agtesa, A., De Brito Silva, G., Dhinakaran, V., & Usman, M. (2020). Simulation of vitiligo therapy equipment. Journal of Robotics and Control (JRC), 1(4), 124–128. https://doi.org/10.18196/jrc.1426
• Wijaya, N. H., Ibrahim, M., Shahu, N., & Sattar, M. U. (2021). Arduino-based digital advanced audiometer. Journal of Robotics and Control (JRC), 2(2), 83–87. https://doi.org/10.18196/jrc.2257
• Wijaya, N. H., Novela, D. F., Shahu, N., & Sattar, M. U. (2020). Arduino-based mini shaker for automatic chemical solution mixer. Journal of Robotics and Control (JRC), 1(6), 220–223. https://doi.org/10.18196/jrc.1641
• Zahid, Z., Sattar, M. U., Khan, H. W., Zahid, A., & Riaz, M. F. (2021). A Smart Analysis and Visualization of The Power Forecasting in Pakistan. International Journal of Computing and Digital Systems, 10(1), 761–771. https://doi.org/10.12785/ijcds/100170