Mohsen Dorraki

Australian Institute for Machine Learning - Operations

Division of Research and Innovation

My Research
Career
Publications
Grants and Funding
Teaching
Contact

Mohsen Dorraki is currently a Lead Machine Learning Scientist at the Australian Institute for Machine Learning (AIML) and South Australian Health and Medical Research (SAHMRI). He completed his PhD studies at the University of Adelaide (UoA), Australia, under the supervision of Prof. Derek Abbott, Dr Andrew Allison and A/Prof. Brendon Coventry on medical machine learning and signal processing, with a prestigious scholarship from the Faculty of Engineering, Computer and Mathematical Sciences (ECMS). He received the M.Sc. degree in image analysis from the Amirkabir University of Technology, Tehran, Iran, in 2011, and the B.Eng. degree in electronics engineering from the Azad University of Birjand, Iran, in 2007.

He received a number of grants and awards, including DIGI+ FAME STRATEGY grant from the University of Adelaide in 2021, Centre for Augmented Reasoning (CAR) Grant from AIML in 2021, Dean's Commendation for Doctoral Thesis Excellence from the University of Adelaide in 2021, the Australian Mathematical Sciences Institute (AMSI) Travel Grant in 2018 and 2020, and DR Stranks Travelling Fellowship, in 2019. Also, he was granted the ECMS Divisional Scholarship from The University of Adelaide to study toward his PhD degree in 2017.

Research Interests

Biomedical Engineering Cancer Therapy Electrical and Electronic Engineering Signal Processing

Journals

Year	Citation
2023	Al-Qadami, G., Bowen, J., Van Sebille, Y., Secombe, K., Dorraki, M., Verjans, J., . . . Le, H. (2023). Baseline gut microbiota composition is associated with oral mucositis and tumour recurrence in patients with head and neck cancer: a pilot study. Supportive Care in Cancer, 31(1), 14 pages. DOI WoS1
2022	Dorraki, M., Muratovic, D., Fouladzadeh, A., Verjans, J., Allison, A., Findlay, D., & Abbott, D. (2022). Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures. DOI
2022	Dorraki, M., Muratovic, D., Fouladzadeh, A., Verjans, J. W., Allison, A., Findlay, D. M., & Abbott, D. (2022). Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures.. PNAS nexus, 1(5), pgac258. DOI
2022	Dorraki, M., Liao, Z., Abbott, D., Psaltis, P., Baker, E., Bidargaddi, N., . . . Verjans, J. (2022). IMPROVING CARDIOVASCULAR DISEASE RISK PREDICTION WITH MACHINE LEARNING USING MENTAL HEALTH DATA: A PROSPECTIVE UK BIOBANK STUDY. DOI
2021	Fouladzadeh, A., Dorraki, M., Min, K. K. M., Cockshell, M. P., Thompson, E. J., Verjans, J. W., . . . Abbott, D. (2021). The development of tumour vascular networks. Communications Biology, 4(1), 1111-1-1111-10. DOI Scopus4 WoS2 Europe PMC1
2020	Dorraki, M., Allison, A., & Abbott, D. (2020). Publisher Correction: Truels and strategies for survival (Scientific Reports, (2019), 9, 1, (8996), 10.1038/s41598-019-45253-5). Scientific Reports, 10(1), 1 page. DOI
2020	Dorraki, M., Fouladzadeh, A., Allison, A., Bonder, C., & Abbott, D. (2020). Angiogenic Networks in Tumors—Insights via Mathematical Modeling. IEEE Access, 8, 43215-43228. DOI Scopus7 WoS6
2020	Lei, Z., ul Haq, A., Dorraki, M., Zhang, D., & Abbott, D. (2020). Composing recipes based on nutrients in food in a machine learning context. Neurocomputing, 415, 382-396. DOI
2019	Dorraki, M., Islam, M. S., Allison, A., & Abbott, D. (2019). Parameter identification using moment of velocity. Royal Society Open Science, 6(11), 190671-1-190671-8. DOI
2019	Dorraki, M., Fouladzadeh, A., Allison, A., Davis, B. R., & Abbott, D. (2019). On moment of velocity for signal analysis. Royal Society Open Science, 6(3), 182001-1-182001-10. DOI Scopus2 WoS2 Europe PMC2
2019	Dorraki, M., Fouladzadeh, A., Salamon, S. J., Allison, A., Coventry, B. J., & Abbott, D. (2019). Can C-reactive protein (CRP) time series forecasting be achieved via deep learning?. IEEE Access, 7, 59311-59320. DOI Scopus6 WoS5
2019	Dorraki, M., Allison, A., & Abbott, D. (2019). Truels and strategies for survival.. Scientific reports, 9(1), 1-7. DOI Scopus2 WoS3 Europe PMC1
2019	Islam, M., Cordeiro, C., Sultana, J., Aoni, R., Feng, S., Ahmed, R., . . . Abbott, D. (2019). A Hi-Bi ultra-sensitive surface plasmon resonance fiber sensor. IEEE Access, 7, 79085-79094. DOI Scopus91 WoS81
2018	Islam, M. S., Sultana, J., Dorraki, M., Atai, J., Islam, M. R., Dinovitser, A., . . . Abbott, D. (2018). Low loss and low dispersion hybrid core photonic crystal fiber for terahertz propagation. Photonic Network Communications, 35(3), 364-373. DOI Scopus36 WoS33
2018	Dorraki, M., Fouladzadeh, A., Salamon, S. J., Allison, A., Coventry, B. J., & Abbott, D. (2018). On detection of periodicity in C-reactive protein (CRP) levels. Scientific Reports, 8(1), 7 pages. DOI Scopus12 WoS10 Europe PMC5
2015	Dorraki, M., Cambrell, G., & Abbott, D. (2015). Analysis of the transient response of a dual-fed RC transmission line. PLoS One, 10(3), e0116993-1-e0116993-11. DOI Scopus2 WoS2 Europe PMC2
2015	Dorraki, M., Cambrell, G., & Abbott, D. (2015). Correction: Analysis of the transient response of a dual-fed RC transmission line. PLoS ONE, 10(3), e0123497-1-e0123497-11. DOI

Conference Papers

Year	Citation
2019	Dorraki, M., Fouladzadeh, A., Allison, A., Coventry, B., & Abbott, D. (2019). Deep Learning for C-Reactive Protein Prediction. In 2018 2nd European Conference on Electrical Engineering and Computer Sciece (EECS) (pp. 1-5). online: IEEE. DOI Scopus1 WoS1
2018	Dorraki, M., Fouladzadeh, A., Allison, A., Coventry, B., & Abbott, D. (2018). Deep learning for C-reactive protein prediction. In Proc. 2018 2nd European Conference on Electrical Engineering and Computer Science (EECS) (pp. 160-164). IEEE: IEEE.
2012	Dorraki, M., Ghidary, S. S., & Menhaj, M. B. (2012). An efficient brush model for real-time oil painting using image processing algorithms. In Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 (pp. 819-823). IEEE. DOI Scopus3