Dr Fida Hasan

Dr Fida Hasan

Lecturer

Teaching and Learning Certification from Harvard University, USA
Doctorate of Philosophy (PhD) from Queensland University of Technology (QUT), Brisbane

UNSW Canberra
School of Professional Studies

Dr. Fida Hasan is an entrepreneurial academic and a Fellow of the Higher Education Academy (FHEA), UK, recognised for his excellence in teaching and supervising higher academia. He is currently working as a Lecturer (in the Commonwealth system, which is equivalent to a North American Assistant professor) in Cyber Security at UNSW. He is an Award-winning Researcher who enjoys practising innovation through teaching. 

Fida Hasan is an expert in a well-balanced set of ICT skills, including Cyber Security, Artificial Intelligence, which gives him the ability to design, build, and implement technical IT solutions with a narrative that is easily communicated to everyone involved. In industry settings, he helped clients from a wide range of sectors leverage ICT to accelerate their organisational growth and secure their digital assets from cyberattacks.

Fida Hasan is OPEN to industry collaboration and welcomes any interest and opportunity to develop real-world solutions. Please reach out to him with your problem and project requirements.

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To Xplore more about Dr. Fida Hasan, please visit his personal website https://www.fidahasan.com
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Over the past years, Dr. Fida Hasan has held various research and leadership positions within Australia and abroad and has received recognition for his commitment, professional accomplishments, and community outreach efforts in the technology, education, and social communities. He is open to offering consultation services.

Fida Hasan is experienced in managing and contributing to cybersecurity projects for government agencies and private sector clients. He served as the theme Post-doc, where he conducted and oversaw projects for the Cyber Security Cooperative Research Centre (CSCRC), a Commonwealth-funded initiative to strengthen the nation's cyber security capabilities.

He has also contributed to and successfully completed federal government-funded projects for the Department of Education, Skills, and Employment (DESE) in relation to the Australian Cyber Security Centre (ACSC). He also delivered projects for the Transport and Main Road (TMR) Queensland Government.


Information for Prospective Research Students

[Future Ph.D. & Master by Research Students]

Ph.D. scholarships ($37,684 per year) are available for both Domestic and International Students high-achieving students (with H1/High Distinction in UG and/or Masters by Research).  If you are motivated, please reach out to Dr. Fida Hasan via email.

Students who are motivated and have backgrounds in Cyber Security (Process and Technology), Computer Science, Data Science, Information Systems, Electronics and Communication, and relevant fields are encouraged to reach to Dr. Fida Hasan and apply for research positions at UNSW. 

  • Several types of scholarships are available, but it is noteworthy to mention that admission and scholarship applications are highly competitive. A general guide on HDR is available here to get a general feel for your competitiveness. For International Candidate, you need to meet the English language requirements.

  • If you are eligible and interested in working on the relevant topics in Dr. Fida’s research domain (or closely related topics), please SEND your CVacademic transcripts, the result of the self-assessment, and a research proposal (less than 6 pages).

  • Your research proposal should highlight: 1) Research motivation; 2) Research problems; 3) Research questions; 4) Research Objectives; 5) Short Review of the most relevant Literature; 6) Proposed Methodology and 7) Expected Outcome

For more information, please refer to the following links on how and when to apply for a research degree. NB: Feel free to reach out with your administrative general questions to the university here and any research-related questions to Dr. Fida Hasan.

  • Journal articles | 2024
    Akter A; Nosheen N; Ahmed S; Hossain M; Yousuf MA; Almoyad MAA; Hasan KF; Moni MA, 2024, 'Robust clinical applicable CNN and U-Net based algorithm for MRI classification and segmentation for brain tumor', Expert Systems with Applications, 238, http://dx.doi.org/10.1016/j.eswa.2023.122347
    Journal articles | 2024
    Hasan KF; Simpson L; Baee MAR; Islam C; Rahman Z; Armstrong W; Gauravaram P; McKague M, 2024, 'A Framework for Migrating to Post-Quantum Cryptography: Security Dependency Analysis and Case Studies', IEEE Access, 12, pp. 23427 - 23450, http://dx.doi.org/10.1109/ACCESS.2024.3360412
    Journal articles | 2024
    Rahman W; Hossain MM; Hasan MM; Iqbal MS; Rahman MM; Fida Hasan K; Moni MA, 2024, 'Automated Detection of Harmful Insects in Agriculture: A Smart Framework Leveraging IoT, Machine Learning, and Blockchain', IEEE Transactions on Artificial Intelligence, 5, pp. 4787 - 4798, http://dx.doi.org/10.1109/TAI.2024.3394799
    Journal articles | 2023
    Hasan KF; Feng Y; Tian YC, 2023, 'Precise GNSS Time Synchronization with Experimental Validation in Vehicular Networks', IEEE Transactions on Network and Service Management, 20, pp. 3289 - 3301, http://dx.doi.org/10.1109/TNSM.2022.3228078
    Journal articles | 2023
    Mim TR; Amatullah M; Afreen S; Yousuf MA; Uddin S; Alyami SA; Hasan KF; Moni MA, 2023, 'GRU-INC: An inception-attention based approach using GRU for human activity recognition', Expert Systems with Applications, 216, http://dx.doi.org/10.1016/j.eswa.2022.119419
    Journal articles | 2023
    Rana MM; Islam MM; Talukder MA; Uddin MA; Aryal S; Alotaibi N; Alyami SA; Hasan KF; Moni MA, 2023, 'A robust and clinically applicable deep learning model for early detection of Alzheimer's', IET Image Processing, 17, pp. 3959 - 3975, http://dx.doi.org/10.1049/ipr2.12910
    Journal articles | 2023
    Talukder MA; Hasan KF; Islam MM; Uddin MA; Akhter A; Yousuf MA; Alharbi F; Moni MA, 2023, 'A dependable hybrid machine learning model for network intrusion detection', Journal of Information Security and Applications, 72, http://dx.doi.org/10.1016/j.jisa.2022.103405
    Journal articles | 2023
    Talukder MA; Islam MM; Uddin MA; Akhter A; Pramanik MAJ; Aryal S; Almoyad MAA; Hasan KF; Moni MA, 2023, 'An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning', Expert Systems with Applications, 230, http://dx.doi.org/10.1016/j.eswa.2023.120534
    Journal articles | 2022
    Bala M; Ali MH; Satu MS; Hasan KF; Moni MA, 2022, 'Efficient Machine Learning Models for Early Stage Detection of Autism Spectrum Disorder', Algorithms, 15, pp. 166 - 166, http://dx.doi.org/10.3390/a15050166
    Journal articles | 2022
    Islam MM; Hossain MB; Akhtar MN; Moni MA; Hasan KF, 2022, 'CNN Based on Transfer Learning Models Using Data Augmentation and Transformation for Detection of Concrete Crack', Algorithms, 15, http://dx.doi.org/10.3390/a15080287
    Journal articles | 2018
    Hasan KF; Feng Y; Tian Y-C, 2018, 'GNSS Time Synchronization in Vehicular Ad-Hoc Networks: Benefits and Feasibility', IEEE Transactions on Intelligent Transportation Systems, 19, pp. 3915 - 3924, http://dx.doi.org/10.1109/tits.2017.2789291
    Journal articles | 2018
    Hasan KF; Wang C; Feng Y; Tian Y-C, 2018, 'Time synchronization in vehicular ad-hoc networks: A survey on theory and practice', Vehicular Communications, 14, pp. 39 - 51, http://dx.doi.org/10.1016/j.vehcom.2018.09.001
  • Preprints | 2020
    Dasanayaka N; Hasan KF; Wang C; Feng Y, 2020, Enhancing Vulnerable Road User Safety: A Survey of Existing Practices and Consideration for Using Mobile Devices for V2X Connections, , http://arxiv.org/abs/2010.15502v2
    Preprints | 2019
    Hasan KF, 2019, Cognitive Internet of Vehicles: Motivation, Layered Architecture and Security Issues, , http://dx.doi.org/10.31224/osf.io/agc43
    Preprints | 2018
    Hasan KF; Feng Y; Tian Y-C, 2018, GNSS Time Synchronization in Vehicular Ad-Hoc Networks: Benefits and Feasibility, http://dx.doi.org/10.1109/TITS.2017.2789291
    Theses / Dissertations |
    Hasan KF, GNSS Time Synchronisation in Co-Operative Vehicular Networks, http://dx.doi.org/10.5204/thesis.eprints.120849