About

I’m Dr Md Mahmudul Hasan, a Senior Lecturer in AI at Anglia Ruskin University in Cambridge, and a member of the Computing, Informatics and Applications Research Group. I completed my PhD in Artificial Intelligence at Anglia Ruskin, funded by the European Union, and hold an MSc in Computer Science from the University of Essex along with a PGCert in Learning and Teaching in Higher Education.

Over the past decade I’ve led several Innovate UK funded projects across very different domains. With Lothian NHS I worked on multimorbidity risk stratification, helping clinicians understand which patients with multiple chronic conditions need the most urgent care. With the Ministry of Cambodia I built a system for fish disease detection — combining computer vision with water-quality analysis to support food security in rural communities. I also led a UKRI Social Ventures project to alleviate loneliness in older people, designing a television-based platform that helps them stay connected with friends and family.

Along the way, I contributed to Bunon — the first native app engine for cross-platform applications — and invented a benchmark for dynamic multi-objective optimisation using deep reinforcement learning, which has since been used by other researchers in the field. I’ve published over 30 peer-reviewed papers in journals and conferences including Engineering Applications of AI, Science of the Total Environment, Sensors, IEEE ICEEICT, AIAI, and SKIMA.

My current work sits at the intersection of artificial intelligence, agentic AI, machine learning, XR technologies, and IT governance. I’m leading several projects on net zero and decarbonisation, including the use of blockchain technologies to bring transparency to supply chains. I’m also exploring quantum-safe cryptography and quantum error correction through projects like QuantoSniff and QuantoTrace, and I serve as the Principal Investigator on AI360Degree, a project elevating fintech security with advanced AI protection and automated compliance.

What I work on

My research interests are deliberately broad, but they share a thread: building data products that solve real problems for real people. I work on:

  • Building data products for healthcare and net zero
  • Robotic Process Automation for healthcare
  • Smart data transformation and consumable AI
  • Deep reinforcement learning
  • Pervasive computing and ambient intelligence, particularly human-agent teamwork
  • Mobile apps and games development across platforms

My areas of expertise include Artificial Intelligence, Data Science, Agentic AI, GenAIOps, AIBOM, Health Informatics, Net Zero Solutions, Responsible AI, and IT Governance.

Teaching and supervision

At ARU I teach Applied Data Analysis & Research Methodology and Software Principles. I currently supervise Sarath Mohan Poyilil, whose PhD is on a conceptual model for optimising hybrid urban systems to achieve net-zero emissions through nature-based solutions.

I welcome PhD enquiries in any of these areas:

  • Building AI and data products for healthcare and net zero
  • Data-driven agentic AI solutions
  • Health informatics
  • Consumable and trustworthy AI
  • AI-enabled smart solutions and AI audit

Memberships

I’m a Fellow of the Higher Education Academy (FHEA), a member of the IEEE and the MCDM (Multiple Criteria Decision Making) Society, an ISO 42001 Lead Auditor for AI Management Systems (AIMS), and a member of the EPSRC Peer Review College.

Selected research grants and consultancy

As Principal Investigator:

  • SBRI: Improving Multimorbidity Acute Care Using Data Analytics (Phase 1) with Lothian NHS — funded by Innovate UK
  • Global cooperation feasibility studies for fish disease detection — funded by Innovate UK
  • SBRI Healthy Ageing Social Ventures: alleviating loneliness for older people — funded by Innovate UK
  • Mindset XR for Digital Mental Health (Strand 1): embedding music therapy for mental wellbeing — funded by Innovate UK
  • QuantoSniff: a next-generation cyber defence using quantum-safe cryptography — KTN, Innovate UK (£12k)
  • AI360Degree: elevating fintech security with advanced AI protection and automated compliance (ai360degree.co.uk)

As Co-Investigator:

  • CYBER ASAP Academic Accelerator Programme (2022) — Innovate UK
  • AI4MultiGIS: AI Integrated Framework for Intelligent Geospatial Handling and Robust Operation in MultiGIS Applications — Chist-Era, EU-funded (2024)
  • Pump Prime: a remotely operated AI decision support system for preterm neonates — QR funding (2023)

As AI Consultant:

  • nanoRail: Non-Intrusive Geotechnical Stability Monitoring System Using Satellite Interferometry — Innovate UK, with the Global Centre of Rail Excellence (2025)

I’ve also received QR funding for Sustainable Futures Research (Green Skills) and Knowledge Exchange policy work.

Selected publications

Journal articles

Yordanov, D., Chakraborty, A., Hasan, M.M., Cirstea, S. (2024). A Framework for Optimising Deep Learning-Based Lane Detection and Steering for Autonomous Driving. Sensors, 24, 8099.

Hazzaa, F., Hasan, M.M., Qashou, A., Yousef, S. (2024). A New Lightweight Cryptosystem for IoT in Smart City Environments. Mesopotamian Journal of CyberSecurity, 4(3), 46–58.

Nanwani, R., Hasan, M., Cirstea, S. (2023). Techniques used to predict climate risks: a brief literature survey. Natural Hazards, 118, 925–951.

Imani, M., Hasan, M.M., Bittencourt, L.F., McClymont, K., Kapelan, Z. (2021). A novel machine learning application: Water quality resilience prediction model. Science of the Total Environment, 768, 144459.

Hasan, M.M., Lwin, K., Imani, M., Shabut, A., Bittencourt, L.F., Hossain, M.A. (2019). Dynamic multi-objective optimisation using deep reinforcement learning: benchmark, algorithm and an application to identify vulnerable zones based on water quality. Engineering Applications of Artificial Intelligence, 86, 107–135.

Conference papers

Hasan, M.M., Rahman, M.M., Ali, M.M., Machado, P. (2024). QuantoTrace: Quantum Error Correction as a Service for Robust Quantum Computing. IEEE ICEEICT, Dhaka.

Khaled, A.A., Hasan, M.M., Islam, S., Papastergiou, S., Mouratidis, H. (2024). Synthetic Data Generation and Impact Analysis of Machine Learning Models for Enhanced Credit Card Fraud Detection. Springer AIAI 2024.

Hasan, M.M., Cirstea, S., Shraboni, M.N. (2023). NeuroXRFitness: Music Therapy for Mental Stress Relief Using EEG Signal. IEEE SKIMA, Kuala Lumpur.

Hasan, M.M., Bitto, A.K., Chakraborty, A., Nanwani, R., Rahman, M.M., Hameed, N. (2023). Net0Chain: An AI-Enabled Climate and Environmental Risks Framework for Achieving Net-Zero. IEEE SKIMA.

Hasan, M.M., Kumar, R., Cirstea, S. (2023). An AI-enabled blockchain-based e-Waste management framework using Non-Fungible Tokens (NFT) to achieve net zero and imply the circular economy. IEEE CryptoEx, Dubai.

Hasan, M.M., Knight, P., Tania, M.H., Bitto, A.K., Das, A., Punja, H. (2022). A Novel Framework for Co-designing an AI-Based Television-enabled Application to Address Social Isolation and Alleviating Loneliness for Older People. IEEE SKIMA.

Gazzard, M., Hicks, Hasan, M.M., Machado, P. (2024). WeedScout: real-time autonomous blackgrass classification and mapping using dedicated hardware. TAROS 2024, London. Springer LNCS.

Mathew, M., Chakraborty, A., Hasan, M., Dhar, A. (2024). Predictive Risk Stratification of Premature Babies Using Machine Learning: A Clinical Decision Support System. ICFSP, Paris.

A full list of publications is available on my Google Scholar profile or via ORCID.