Dr Mohsen Dorraki
Grant-Funded Researcher
Australian Institute for Machine Learning - Projects
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
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.
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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 : official journal of the Multinational Association of Supportive Care in Cancer, 31(1), 98.
Scopus11 WoS5 Europe PMC92022 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.
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), pgac258-1-pgac258-11.
Scopus12022 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.
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.
Scopus11 WoS7 Europe PMC52020 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.
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.
Scopus8 WoS72020 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.
Scopus4 WoS12019 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.
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.
Scopus3 WoS2 Europe PMC22019 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.
Scopus7 WoS62019 Dorraki, M., Allison, A., & Abbott, D. (2019). Truels and strategies for survival.. Scientific reports, 9(1), 1-7.
Scopus5 WoS3 Europe PMC22019 Islam, M. S., Cordeiro, C. M. B., Sultana, J., Aoni, R. A., Feng, S., Ahmed, R., . . . Abbott, D. (2019). A Hi-Bi ultra-sensitive surface plasmon resonance fiber sensor. IEEE Access, 7, 79085-79094.
Scopus120 WoS1012018 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.
Scopus40 WoS362018 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.
Scopus15 WoS13 Europe PMC72015 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.
Scopus2 WoS2 Europe PMC22015 Dorraki, M., Cambrell, G. K., & Abbott, D. (2015). Correction: Analysis of the transient response of a dual-fed RC transmission line. PLoS ONE, 10(3), e0123497-1-e0123497-11.
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Book Chapters
Year Citation 2023 Dorraki, M., Sengupta, P. P., & Verjans, J. W. (2023). Artificial intelligence in echocardiography. In A. C. Chang, A. Limon, R. Brisk, F. Lopez-Jimenez, & L. Y. Sun (Eds.), Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine (pp. 179-184). Elsevier.
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Conference Papers
Year Citation 2023 Wardill, H., van Groningen, L., Molendijk, E., Ferreira, A. R. D. S., Kurilshikov, A., Dorraki, M., . . . Blijlevens, N. (2023). THE CHICKEN AND THE EGG: UNRAVELLING THE FACTORS THAT SHAPE GUT DYSBIOSIS IN HSCT RECIPIENTS. In BONE MARROW TRANSPLANTATION Vol. 58 (pp. 127-128). ELECTR NETWORK: SPRINGERNATURE. 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.
Scopus1 WoS12018 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.
Scopus3
- DIGI+ FAME STRATEGY grant from the University of Adelaide (2021).
- Centre for Augmented Reasoning (CAR) grant from AIML (2021).
- The Australian Mathematical Sciences Institute (AMSI) Travel Grant (2020).
- DR Stranks Travelling Fellowship (2019).
- The Australian Mathematical Sciences Institute (AMSI) Travel Grant (2018).
- ECMS Divisional Scholarship from the University of Adelaide (2017-2021).
2020, Digital Signal Processing, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2020, Project Management, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2020, Electronic Systems, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2020, Analog Electronics, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2020, Electronic Systems, demonstration, School of Electrical & Electronic Engineering - University of Adelaide
2020, Analog Electronics, demonstration, School of Electrical & Electronic Engineering - University of Adelaide
2019, Digital Signal Processing, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2019, Project Management, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2019, Communication IV, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
2019, Electronic Systems, demonstration, School of Electrical & Electronic Engineering - University of Adelaide
2019, Analog Electronics, demonstration, School of Electrical & Electronic Engineering - University of Adelaide
2018, Communication IV, tutorial, School of Electrical & Electronic Engineering - University of Adelaide
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2024 Co-Supervisor Causal discovery and Out-of-Distribution generalization: sampling from posterior over causal graphs Doctor of Philosophy Doctorate Full Time Mr Nadhir Hassen 2024 Co-Supervisor Pre-trained multimodel model for integrated healthcare decision support Doctor of Philosophy Doctorate Full Time Ms Nanyu Dong
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