Overview
Background
Dr Moni holds a PhD in Artificial Intelligence & Data Science in 2014 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, University of Sydney Vice-chancellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined UQ in 2021. He also worked as an assistant professor and lecturer in two universities (PUST and JKKNIU) from 2007 to 2011. He is an Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep learning models to increase the performance and transparency of AI-based automated decision-making systems.
His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving humans explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including stroke MRI/fMRI imaging, real-time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid the diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. His research interest also includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data, especially medical images, neuroimaging (MRI, fMRI, Ultrasound, X-Ray), EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.
- I am currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.
Availability
- Dr Mohammad Ali Moni is:
- Available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, University of Cambridge
Research interests
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Artificial Intelligence, Computer Vision, Machine Learning, Deep-Learning
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Medical Imaging, Medical Image Analysis, Neuro Imaging
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Digital Health, Data Science, Health Informatics, Clinical Informatics
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Data Mining, Text Mining, Natural Language Processing
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Bioinformatics, Systems Biology, Computational Biology
Research impacts
During the last 5 years he has puvblished over 200 journal articles in many top tier journals including The Lancet, Jama Oncology. The impact of his research is evidenced by the high number of citations to his work (>12000 citations, i10-index 157 and an h-index of 50 according to Google Scholar), received $1.89 M as CI-A (8.9 M total) and awards including :
- Best Impact Award in International Conference on Applied Intelligence and Informatics, UK July 30-31, 2021
- University of Wollongong Engineering & information science Distinguished Early Career Fellowship.2019-2020
- Certara-Monash Fellowship Awarded ($2,00,000), Certara Australia Pty. Ltd, 2019
- Seed funding from two companies Karte Ltd (Japan) and iHealthOmics Ltd (Hong Kong) to develop AI-based health-care related software products. Received seed funding ($40,000) from Karte Ltd. 2018-2020
- USyd DVC Research Fellowship ($50,000), University of Sydney2017-2020
- The Ridley Ken Davies Award ($50,000)-- utilising the research data obtained through Dubbo Osteoporosis Epidemiological Study, Ridley Corporation, Australia 2016
- Travel award to attend ANZBMS Conference, Australia, 2016
- Best student paper award in international conference- IDBSS2014, UK2014
- Travel award to attend NIMBioS Modeling, University of Tennessee, USA. 2013
- The Cambridge Commonwealth, European & International Trust award, The Commonwealth Trust, UK 2011
Works
Search Professor Mohammad Ali Moni’s works on UQ eSpace
2024
Journal Article
Multi-view soft attention-based model for the classification of lung cancer-associated disabilities
Esha, Jannatul Ferdous, Islam, Tahmidul, Pranto, Md. Appel Mahmud, Borno, Abrar Siam, Faruqui, Nuruzzaman, Yousuf, Mohammad Abu, Azad, AKM, Al-Moisheer, Asmaa Soliman, Alotaibi, Naif, Alyami, Salem A. and Moni, Mohammad Ali (2024). Multi-view soft attention-based model for the classification of lung cancer-associated disabilities. Diagnostics, 14 (20) 2282, 2282. doi: 10.3390/diagnostics14202282
2024
Journal Article
An improved K-means clustering algorithm towards an efficient data-driven modeling
Zubair, Md., Iqbal, Md. Asif, Shil, Avijeet, Chowdhury, M. J.M., Moni, Mohammad Ali and Sarker, Iqbal H. (2024). An improved K-means clustering algorithm towards an efficient data-driven modeling. Annals of Data Science, 11 (5), 1525-1544. doi: 10.1007/s40745-022-00428-2
2024
Journal Article
A robust deep-learning model to detect major depressive disorder utilising EEG signals
Anik, Israq Ahmed, Kamal, A H M, Kabir, Muhammad Ashad, Uddin, Shahadat and Moni, Mohammad Ali (2024). A robust deep-learning model to detect major depressive disorder utilising EEG signals. IEEE Transactions on Artificial Intelligence, 5 (10), 4938-4947. doi: 10.1109/tai.2024.3394792
2024
Journal Article
Advances in artificial intelligence and blockchain technologies for early detection of human diseases
Shammi, Shumaiya Akter, Ghosh, Pronab, Sutradhar, Ananda, Shamrat, F. M. Javed Mehedi, Moni, Mohammad Ali and Oliveira, Thiago Eustaquio Alves de (2024). Advances in artificial intelligence and blockchain technologies for early detection of human diseases. IEEE Transactions on Computational Social Systems, 12 (1), 210-237. doi: 10.1109/tcss.2024.3449748
2024
Journal Article
Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques
Sutradhar, Ananda, Akter, Sharmin, Shamrat, F M Javed Mehedi, Ghosh, Pronab, Zhou, Xujuan, Idris, Mohd Yamani Idna Bin, Ahmed, Kawsar and Moni, Mohammad Ali (2024). Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques. Heliyon, 10 (17) e36556, e36556. doi: 10.1016/j.heliyon.2024.e36556
2024
Journal Article
Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021
Han, Hannah, Letourneau, Ian D, Abate, Yohannes Habtegiorgis, Abdelmasseh, Michael, Abu-Gharbieh, Eman, Adane, Tigist Demssew, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmadi, Ali, Ahmed, Ayman, Alhalaiqa, Fadwa Naji, Al-Sabah, Salman Khalifah, Al-Worafi, Yaser Mohammed, Amu, Hubert, Andrei, Catalina Liliana, Anoushiravani, Amir, Arabloo, Jalal, Aravkin, Aleksandr Y, Ashraf, Tahira, Azadnajafabad, Sina, Baghcheghi, Nayereh, Bagherieh, Sara, Bantie, Berihun Bantie, Bardhan, Mainak, Basile, Guido, Bayleyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Bekele, Alehegn, Bhojaraja, Vijayalakshmi S ... Dirac, M Ashworth (2024). Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021. The Lancet Gastroenterology and Hepatology, 9 (9), 825-858. doi: 10.1016/S2468-1253(24)00157-2
2024
Journal Article
Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021
Sirota, Sarah Brooke, Doxey, Matthew C, Dominguez, Regina-Mae Villanueva, Bender, Rose Grace, Vongpradith, Avina, Albertson, Samuel B, Novotney, Amanda, Burkart, Katrin, Carter, Austin, Abdi, Parsa, Abdoun, Meriem, Abebe, Ayele Mamo, Abegaz, Kedir Hussein, Aboagye, Richard Gyan, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abualruz, Hasan, Abu-Gharbieh, Eman, Aburuz, Salahdein, Adane, Mesafint Molla, Addo, Isaac Yeboah, Adekanmbi, Victor, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afzal, Muhammad Sohail, Afzal, Saira, Ahinkorah, Bright Opoku, Ahmad, Sajjad, Ahmed, Ayman ... GBD 2021 Upper Respiratory Infections Otitis Media Collaborators (2024). Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021. The Lancet Infectious Diseases, 25 (1), 36-51. doi: 10.1016/s1473-3099(24)00430-4
2024
Journal Article
Automated detection of harmful insects in agriculture: a smart framework leveraging IoT, machine learning, and blockchain
Rahman, Wahidur, Hossain, Muhammad Minoar, Hasan, Md. Mahedi, Iqbal, Md. Sadiq, Rahman, Mohammad Motiur, Fida Hasan, Khondokar and Moni, Mohammad Ali (2024). Automated detection of harmful insects in agriculture: a smart framework leveraging IoT, machine learning, and blockchain. IEEE Transactions on Artificial Intelligence, 5 (9), 4787-4798. doi: 10.1109/tai.2024.3394799
2024
Journal Article
MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool
Sultan, Md. Fahim, Shaon, Md. Shazzad Hossain, Karim, Tasmin, Ali, Md. Mamun, Hasan, Md. Zahid, Ahmed, Kawsar, Bui, Francis M., Chen, Li, Dhasarathan, Vigneswaran and Moni, Mohammad Ali (2024). MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool. Heliyon, 10 (18) e37820, e37820. doi: 10.1016/j.heliyon.2024.e37820
2024
Conference Publication
Identifying predictors of physical activity and walking outcomes after stroke through a machine learning approach
Nayak, Neelam, Mahendran, Niruthikha, Moni, Mohammad, Kuys, Suzanne and Brauer, Sandra (2024). Identifying predictors of physical activity and walking outcomes after stroke through a machine learning approach. Asia Pacific Stroke Conference 2024 Combined Australian and New Zealand Stroke Organisation Conference, Adelaide, SA, Australia, 25–28 September 2024. Basel, Switzerland: S. Karger.
2024
Journal Article
Global pattern, trend, and cross-country inequality of early musculoskeletal disorders from 1990 to 2019, with projection from 2020 to 2050
Wu, Dongze, Jin, Yingzhao, Guo, Cui, Abbasian, Mohammadreza, Abbasifard, Mitra, Abbott, J. Haxby, Abdullahi, Auwal, Abedi, Aidin, Abidi, Hassan, Abolhassani, Hassan, Abu-Gharbieh, Eman, Aburuz, Salahdein, Abu-Zaid, Ahmed, Addo, Isaac Yeboah, Adegboye, Oyelola A., Adepoju, Abiola Victor, Adikusuma, Wirawan, Adnani, Qorinah Estiningtyas Sakilah, Aghamiri, Shahin, Ahmad, Danish, Ahmed, Ayman, Aithala, Janardhana P., Akhlaghi, Shiva, Akkala, Sreelatha, Alalwan, Tariq A., Albashtawy, Mohammed, Alemi, Hediyeh, Alhalaiqa, Fadwa Alhalaiqa Naji, Ali, Endale Alemayehu ... Wu, Dongze (2024). Global pattern, trend, and cross-country inequality of early musculoskeletal disorders from 1990 to 2019, with projection from 2020 to 2050. Med, 5 (8), 943-962. doi: 10.1016/j.medj.2024.04.009
2024
Journal Article
Global estimates on the number of people blind or visually impaired by age-related macular degeneration: a meta-analysis from 2000 to 2020
Furtado, João M., Jonas, Jost B., Tapply, Ian, Fernandes, Arthur G., Cicinelli, Maria Vittoria, Arrigo, Alessandro, Leveziel, Nicolas, Resnikoff, Serge, Taylor, Hugh R., Sedighi, Tabassom, Flaxman, Seth, Battaglia Parodi, Maurizio, Bikbov, Mukkharram M., Braithwaite, Tasanee, Bron, Alain, Cheng, Ching-Yu, Congdon, Nathan, Del Monte, Monte A., Ehrlich, Joshua R., Fricke, Tim, Friedman, David, Gazzard, Gus, Hartnett, M. Elizabeth, Kahloun, Rim, Kempen, John H., Khairallah, Moncef, Khanna, Rohit C., Kim, Judy E., Lansingh, Van Charles ... Bourne, Rupert R. A. (2024). Global estimates on the number of people blind or visually impaired by age-related macular degeneration: a meta-analysis from 2000 to 2020. Eye, 38 (11), 2070-2082. doi: 10.1038/s41433-024-03050-z
2024
Journal Article
Global, regional, and national burden of gout, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021
Cross, Marita, Ong, Kanyin Liane, Culbreth, Garland T, Steinmetz, Jaimie D, Cousin, Ewerton, Lenox, Hailey, Kopec, Jacek A, Haile, Lydia M, Brooks, Peter M, Kopansky-Giles, Deborah R, Dreinhoefer, Karsten E, Betteridge, Neil, Abbasian, Mohammadreza, Abbasifard, Mitra, Abedi, Aidin, Aboye, Melka Biratu, Aravkin, Aleksandr Y, Artaman, Al, Banach, Maciej, Bensenor, Isabela M, Bhagavathula, Akshaya Srikanth, Bhat, Ajay Nagesh, Bitaraf, Saeid, Buchbinder, Rachelle, Burkart, Katrin, Chu, Dinh-Toi, Chung, Sheng-Chia, Dadras, Omid, Dai, Xiaochen ... Woolf, Anthony D (2024). Global, regional, and national burden of gout, 1990–2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. The Lancet Rheumatology, 6 (8), e507-e517. doi: 10.1016/S2665-9913(24)00117-6
2024
Journal Article
The relationship between hair cortisol concentration and autism diagnosis
Lin, Ping-I, John, James Rufus, Masi, Anne, Ong, Lin Kooi, Mathew, Nisha E., Moni, Mohammed Ali, Eapen, Valsamma and Walker, Adam K. (2024). The relationship between hair cortisol concentration and autism diagnosis. Journal of Psychiatric Research, 176, 68-76. doi: 10.1016/j.jpsychires.2024.05.052
2024
Journal Article
An effective screening of COVID‐19 pneumonia by employing chest X‐ray segmentation and attention‐based ensembled classification
Sayeed, Abu, Khansur, Nasif Osman, Srizon, Azmain Yakin, Faruk, Md. Farukuzzaman, Alyami, Salem A., Azad, AKM and Moni, Mohammad Ali (2024). An effective screening of COVID‐19 pneumonia by employing chest X‐ray segmentation and attention‐based ensembled classification. IET Image Processing, 18 (9), 2400-2416. doi: 10.1049/ipr2.13106
2024
Journal Article
Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR‐mutated lung adenocarcinoma
Bhattacharjya, Abanti, Islam, Md Manowarul, Uddin, Md Ashraf, Talukder, Md Alamin, Azad, AKM, Aryal, Sunil, Paul, Bikash Kumar, Tasnim, Wahia, Almoyad, Muhammad Ali Abdulllah and Moni, Mohammad Ali (2024). Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR‐mutated lung adenocarcinoma. FEBS Open Bio, 14 (7), 1166-1191. doi: 10.1002/2211-5463.13807
2024
Journal Article
An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection
Mehedi Shamrat, F. M. Javed, Shakil, Rashiduzzaman, Sharmin,, Hoque ovy, Nazmul, Akter, Bonna, Ahmed, Md Zunayed, Ahmed, Kawsar, Bui, Francis M. and Moni, Mohammad Ali (2024). An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection. Healthcare Analytics, 5 100303, 100303. doi: 10.1016/j.health.2024.100303
2024
Journal Article
Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021
GBD 2021 Risk Factors Collaborators, Mamun, Abdullah A., Anderlini, Deanna, Chung, Eric, Ferrari, Alize J., Santomauro, Damian Francesco, Kanmiki, Edmund Wedam, Maravilla, Joemer C., Khan, Asaduzzaman, Moni, Mohammad Ali, McGrath, John J. and Sartorius, Benn (2024). Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403 (10440), 2162-2203. doi: 10.1016/S0140-6736(24)00933-4
2024
Journal Article
Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021
Vollset, Stein Emil, Ababneh, Hazim S., Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbasgholizadeh, Rouzbeh, Abbasian, Mohammadreza, Abbastabar, Hedayat, Abd Al Magied, Abdallah H. A., Abd ElHafeez, Samar, Abdelkader, Atef, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdi, Parsa, Abdollahi, Mohammad, Abdoun, Meriem, Abdullahi, Auwal, Abebe, Mesfin, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Abouzid, Mohamed, Aboye, Girma Beressa, Abreu, Lucas Guimaraes, Absalan, Abdorrahim, Abualruz, Hasan, Abubakar, Bilyaminu, Abukhadijah, Hana Jihad Jihad, Addolorato, Giovanni, Adekanmbi, Victor ... GBD 2021 Forecasting Collaborators (2024). Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021. The Lancet, 403 (10440), 2204-2256.
2024
Journal Article
Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Ferrari, Alize J., Santomauro, Damian Francesco, Aali, Amirali, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbastabar, Hedayat, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdollahi, Arash, Abdullahi, Auwal, Abegaz, Kedir Hussein, Abeldaño Zuñiga, Roberto Ariel, Aboagye, Richard Gyan, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abualruz, Hasan, Abu-Gharbieh, Eman, Abu-Rmeileh, Niveen ME, Ackerman, Ilana N, Addo, Isaac Yeboah, Addolorato, Giovanni, Adebiyi, Akindele Olupelumi, Adepoju, Abiola Victor, Adewuyi, Habeeb Omoponle, Afyouni, Shadi, Afzal, Saira, Afzal, Sina, Agodi, Antonella ... Murray, Christopher J L (2024). Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403 (10440), 2133-2161. doi: 10.1016/s0140-6736(24)00757-8
Supervision
Availability
- Dr Mohammad Ali Moni is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
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Deep learning models development and application to the Neuro Imaging (MRI and fMRI)
Magnetic resonance (MR) imaging has become an important non-invasive radiological modality for various clinical applications, such as stoke and cancer. Extracting meaningful clinical information without human interaction is a challenging task. Developing such automatic methods are important in order to reduce human errors and the time taken by clinicians.
In this project, the student will develop novel deep learning algorithms to solve segmentation and detection problems from imaging that could possibly be deployed to MRI & fMRI scanners and may eventually used for diagnostic purposes. The project will involve applying computer vision and deep learning techniques to MR image processing and analysis.
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Deep Leaning Model to identify Neuroimaging biomarkers
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Deep Learning models to solve inverse problems utiling MRI/fMRI image
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AI-based based model development for Magnetic Resonance Imaging
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AI-based Model development for ECG/EEG study
Supervision history
Current supervision
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Doctor Philosophy
Robust and Explainable AI to Solve Clinical Problems
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan
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Doctor Philosophy
Coloured noise estimation using electroencephalogram data and deep-learning method for improvement of cognitive function
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan
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Doctor Philosophy
Wearable devices and AI Models for Monitoring, Predicting and Assessment Post-stroke Recovery
Principal Advisor
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Master Philosophy
Quantum Deep Learning for Brain Informatics
Principal Advisor
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Doctor Philosophy
Developing AI-based Discission Support System utilising multimodal data
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan
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Doctor Philosophy
Managing non-communicable diseases (NCDs) to achieve Universal Health Coverage (UHC) in South Asia: A case study from Bangladesh
Associate Advisor
Other advisors: Associate Professor Asaduzzaman Khan
Completed supervision
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2025
Doctor Philosophy
Understanding the pathophysiology of stroke using bioinformatics and statistical genetics
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan, Dr Jian Zeng
Media
Enquiries
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