Dr Sazid Hasan
Research Officer
School of Electrical Engineering and Computer Science
Book Chapter
Hasan, Sazid, Islam, Md Musfiqul, Ahmed, Firoz, Saabit, S. M. Mustahsin, Nafi, Nazmus Shaker, Hasan, Mohammad Kamrul, Islam, Shayla and Memon, Imran (2022). Performance analysis of modulation techniques over a smart city optical communication channel under weak atmospheric turbulence. IoT and WSN based smart cities: a machine learning perspective. (pp. 195-213) edited by Shalli Rani, Vyasa Sai and R. Maheswar. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-84182-9_12
Journal Articles
Hasan, Sazid, Brankovic, Aida, Awal, Md Abdul, Rezaeieh, Sasan Ahdi, Keating, Shelley E., Abbosh, Amin M. and Zamani, Ali (2024). HepNet: deep neural network for classification of early-stage hepatic steatosis using microwave signals. IEEE Journal of Biomedical and Health Informatics, 29 (1), 142-151. doi: 10.1109/jbhi.2024.3489626
Hasan, Sazid, Zamani, A., Brankovic, A., Bialkowski, K. and Abbosh, A. M. (2023). Stroke Classification with Microwave Signals using Explainable Wavelet Convolutional Neural Network. IEEE Journal of Biomedical and Health Informatics, 28 (10), 1-10. doi: 10.1109/jbhi.2023.3327296
Conference Papers
Hasan, Sazid, Zamani, Ali, Awal, Md Abdul and Abbosh, Amin (2024). Scaled wavelet for hepatic steatosis classification using microwave signals. 2024 IEEE International Symposium on Antennas and Propagation and INC/USNC‐URSI Radio Science Meeting (AP-S/INC-USNC-URSI), Firenze, Italy, 14-19 July 2024. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ap-s/inc-usnc-ursi52054.2024.10686529
Saabit, S. M. Mustahsin, Hasan, Sazid and Chowdhury, Nafis Ahmed (2021). Virtual Power Plant Implementation and Cost Minimization for Retail Industry. 2021 2nd International Conference for Emerging Technology (INCET), Belagavi, India, 21-23 May 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/incet51464.2021.9456399
Thesis
Hasan, Sazid (2025). Microwave medical imaging and classification: a deep learning approach validated with experimental and clinical data. PhD Thesis, School of Electrical Engineering and Computer Science, The University of Queensland. doi: 10.14264/3145058