Biography
Dr Md Zakir Hossain is a Lecturer in the School of Systems and Computing at UNSW Canberra. His research brings together artificial intelligence, cybersecurity, and human-centred computing to develop trustworthy and practical solutions for health, safety, and secure digital systems. His interests include machine learning, large language models, multimodal learning, affective computing, explainable AI, and privacy-preserving methods.
He holds a...view more
Dr Md Zakir Hossain is a Lecturer in the School of Systems and Computing at UNSW Canberra. His research brings together artificial intelligence, cybersecurity, and human-centred computing to develop trustworthy and practical solutions for health, safety, and secure digital systems. His interests include machine learning, large language models, multimodal learning, affective computing, explainable AI, and privacy-preserving methods.
He holds a PhD in Computer Science from the Australian National University and has held research and academic positions at ANU, Curtin University, CSIRO, and Macquarie University. He collaborates with academic, government, industry, healthcare, and community partners, including Seeing Machines, NatRoad Australia, Encompass Australia, SalTas, Fiona Stanley Hospital, and Perth Blood Institute. His research received the Best Application Paper Award at IEEE/CVF WACV 2023. With more than a decade of university teaching and research supervision experience, Dr Hossain is committed to research-led education and responsible AI innovation. He is an Associate Fellow of the Higher Education Academy (AFHEA).
For further details (summary below), please visit his personal website.
My Grants
Selected Research Grants
- 2025–2026 | Co-Chief Investigator: AI-based Fatigue Monitoring System for Heavy Vehicle Safety. National Heavy Vehicle Regulator, Heavy Vehicle Safety Initiative. Total project funding: $359,985.
- 2025 | Lead Chief Investigator: AI-Driven Cognitive Augmentation and Decision Support for Defence and National Security. Defence Artificial Intelligence Research Network (DAIRNet) Research Collaboration Grant. Funding: $5,000.
- 2024 | Co-Chief Investigator: Design and Development of a 3D-printed MEMS-based Stethoscope for Real-time Heart Monitoring and Cardiovascular Disease Prediction Using Machine Learning to Assist Medical Professionals. BRAC University Research Seed Grant, Bangladesh. Funding: $8,000.
- 2023 | Lead/Co-Chief Investigator: Future Health Research and Innovation (FHRI) Fund—Generative AI for WA Health and Medical Challenges. Combined funding: $150,000, across three projects:
- Generating Ultrasound Images — Lead Chief Investigator.
- Generative AI to Create High Veracity Enlarged X-ray Abnormalities for Medical Training — Lead Chief Investigator.
- Enabling Efficient and Clinically Accurate Multimodal Examinations of Chest Diseases — Co-Chief Investigator.
My Qualifications
Academic Qualifications
- PhD in Computer Science, Australian National University, Canberra, Australia, 2019.
- Master of Science in Electrical and Electronic Engineering, Khulna University of Engineering & Technology (KUET), Bangladesh, 2014.
- Bachelor of Science in Electrical and Electronic Engineering, Khulna University of Engineering & Technology (KUET), Bangladesh, 2011.
Professional Qualifications
- MicroMasters in Cloud Computing, University of Maryland Global Campus, USA, 2023.
- Associate Fellow of the Higher Education Academy (AFHEA), 2019.
My Awards
- 2025 — Best Publication, HDR Forum Award, School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University. Recognised publication: Empathy Detection from Text, Audiovisual, Audio or Physiological Signals: A Systematic Review of Task Formulations and Machine Learning Methods.
- 2025 — Third Place (Team Award), AI4PAIN 2025, Second Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment. Awarded paper: Painthenticate: Feature Engineering on Multimodal Physiological Signals.
- 2024 — Tony’s Award for the Most Obscure Title or Bingo Word, International Conference on Digital Image Computing: Techniques and Applications (DICTA). Awarded paper: Paraconsistent Abductive Learning for Processing Inconsistent Information
- 2023 — Best Application Paper Award, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Awarded paper: Exemplar Guided Deep Neural Network for Spatial Transcriptomics Analysis of Gene Expression Prediction.
My Research Activities
Dr Hossain investigates how AI systems can make reliable predictions, understand human behaviour, and support decisions while protecting privacy and security. He welcomes partnerships with industry, healthcare, and government organisations to address applied challenges and develop collaborative funding proposals. His research focuses on:
- AI and cybersecurity: Intrusion and anomaly detection, generalisation of machine learning models across security datasets, and the robustness and security of AI systems.
- Trustworthy language models and AI agents: Reliability, explainability, fairness, and privacy, with applications in healthcare knowledge and personality assessment.
- Multimodal and affective computing: Integrating text, audio, video, physiological, and behavioural signals to model empathy, engagement, emotion, personality, and fatigue.
- AI for health and safety: Medical and physiological data analysis, digital health monitoring, and driver engagement and fatigue assessment.
My Research Supervision
Areas of supervision
Dr Hossain welcomes enquiries from prospective PhD, master’s by research, and honours students interested in:
- Trustworthy and explainable artificial intelligence.
- Multimodal learning, affective computing, and human behaviour modelling.
- AI for cybersecurity, intrusion detection, and privacy-preserving learning.
- Large language models, Computer vision, generative AI, and AI agents.
- AI applications in digital health, driver monitoring, and safety.
Applicants with strong academic results, programming skills, and an interest in interdisciplinary research are encouraged to get in touch. Relevant research experience and clear written and verbal communication skills are valued.
Interested students should provide:
- A CV and academic transcripts.
- A brief statement of research interests.
- A preliminary research proposal outlining the problem, relevant literature, research questions, proposed methods, expected contributions, and timeline.
Eligible applicants may apply for competitive UNSW research scholarships. Admission and scholarship outcomes depend on academic merit, eligibility, and available funding. Applicants should review UNSW’s English language requirements, research degree application guidance, and application dates.
My Teaching
Dr Hossain teaches across artificial intelligence, cybersecurity, networking, human–computer interaction, and programming. His experience includes face-to-face, hybrid, and online delivery, alongside lecture development, course updates, and assessment design.
Selected teaching experience
- Networked Information Systems (COMP2410/6340), The Australian National University.
- Neural Networks, Deep Learning and Bio-inspired Computing (COMP4660/8420), The Australian National University.
- Human Computer Interface Design and Evaluation (COMP3900/6390), The Australian National University.
- Database Systems (COMP2400/6240), Shandong University.
- Programming for Scientists (COMP1730/6730), The Australian National University.
Curriculum contributions
- Development of a micro-credential module on Ethical Dimensions of AI: Bias, Fairness, and Transparency at Curtin University.
- External review of the Bachelor of Technology in Artificial Intelligence curriculum at SAI University.
- Networked Information Systems (COMP2410/6340) at The Australian National University.