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
2025
Journal Article
Understanding Neurocognition with Deep Learning and MRI: A Systematic Review
Rahman, Md. Tanvir, Orka, Nabil Anan, Khan, Asaduzzaman, Liò, Pietro and Moni, Mohammad Ali (2025). Understanding Neurocognition with Deep Learning and MRI: A Systematic Review. IEEE Transactions on Cognitive and Developmental Systems, PP (99), 1-17. doi: 10.1109/tcds.2025.3635161
2025
Journal Article
Global, regional, and national progress towards the 2030 global nutrition targets and forecasts to 2050: a systematic analysis for the Global Burden of Disease Study 2021
Arndt, Michael Benjamin, Abate, Yohannes Habtegiorgis, Abbasi-Kangevari, Mohsen, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdulah, Deldar Morad, Abdulkader, Rizwan Suliankatchi, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Abtew, Yonas Derso, Abu-Gharbieh, Eman, Abu-Rmeileh, Niveen ME, Acuna, Juan Manuel, Adamu, Kidist, Adane, Denberu Eshetie, Addo, Isaac Yeboah, Adeyinka, Daniel Adedayo, Adnani, Qorinah Estiningtyas Sakilah, Afolabi, Aanuoluwapo Adeyimika, Afrashteh, Fatemeh, Afzal, Saira, Agodi, Antonella, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmad, Sajjad, Ahmad, Tauseef ... Reiner, Robert C (2025). Global, regional, and national progress towards the 2030 global nutrition targets and forecasts to 2050: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 404 (10471), 2543-2583. doi: 10.1016/S0140-6736(24)01821-X
2025
Conference Publication
IoT-Enabled Health Assistance for Post-disaster Scenarios
Hossain, Soikat, Sarkar, Ratna R., Yousuf, Mohammad Abu and Moni, Mohammad Ali (2025). IoT-Enabled Health Assistance for Post-disaster Scenarios. Trends in Electronics and Health Informatics TEHI 2023, Dhaka, Bangladesh, 26–27 December 2023. Singapore: Springer. doi: 10.1007/978-981-97-3937-0_44
2025
Book Chapter
A Multi-BranchCNN-LSTM Based Human Activity Recognition Using Wearable and Smartphone Sensors
Khatun, Mst. Alema, Yousuf, Mohammad Abu and Moni, Mohammad Ali (2025). A Multi-BranchCNN-LSTM Based Human Activity Recognition Using Wearable and Smartphone Sensors. Intelligent Networks and Systems: Advanced Technologies and Applications. (pp. 27-39) CRC Press. doi: 10.1201/9781032659770-3
2025
Journal Article
Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: a comprehensive review of COVID-19 detection
Islam, Md Shofiqul, Hasan, Khondokar Fida, Shajeeb, Hasibul Hossain, Rana, Humayan Kabir, Rahman, Md. Saifur, Hasan, Md. Munirul, Azad, AKM, Abdullah, Ibrahim and Moni, Mohammad Ali (2025). Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: a comprehensive review of COVID-19 detection. AI Open, 6, 12-44. doi: 10.1016/j.aiopen.2025.01.003
2025
Book
Graphene in wearable sensors for health monitoring
Debnath, Sourabhi, Debnath, Tanmoy, Moni, Mohammad Ali and Paul, Manoranjan (2025). Graphene in wearable sensors for health monitoring. Singapore: Springer. doi: 10.1007/978-981-96-8850-0
2025
Book Chapter
Explainable AI-Based Heart Attack Prediction Model Using Various Machine Learning and Ensemble Learning Approaches
Palash, Md Istakiak Adnan, Rahman, Muntarin, Yousuf, Mohammad Abu and Moni, Mohammad Ali (2025). Explainable AI-Based Heart Attack Prediction Model Using Various Machine Learning and Ensemble Learning Approaches. Applied Intelligence for Healthcare Informatics: Techniques and Applications. (pp. 1-13) CRC Press. doi: 10.1201/9781003583363-1
2025
Journal Article
Corrections to “Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study”
Raisa, Roksana Akter, Rodela, Ayesha Siddika, Yousuf, Mohammad Abu, Azad, Akm, Alyami, Salem A., Liò, Pietro, Islam, Md Zahidul, Pogrebna, Ganna and Moni, Mohammad Ali (2025). Corrections to “Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study”. IEEE Access, 13, 48033-48033. doi: 10.1109/access.2025.3551391
2024
Journal Article
Burden of disease scenarios by state in the USA, 2022-50: a forecasting analysis for the Global Burden of Disease Study 2021
Mokdad, Ali H., Bisignano, Catherine, Hsu, Johnathan M., Bryazka, Dana, Cao, Shujin, Bhattacharjee, Natalia V., Dalton, Bronte E., Lindstedt, Paulina A., Smith, Amanda E., Ababneh, Hazim S., Abbasgholizadeh, Rouzbeh, Abdelkader, Atef, Abdi, Parsa, Abiodun, Olugbenga Olusola, Aboagye, Richard Gyan, Abukhadijah, Hana J., Abu-Zaid, Ahmed, Acuna, Juan Manuel, Addo, Isaac Yeboah, Adekanmbi, Victor, Adeyeoluwa, Temitayo Esther, Adzigbli, Leticia Akua, Afolabi, Aanuoluwapo Adeyimika, Afrashteh, Fatemeh, Agyemang-Duah, Williams, Ahmad, Shahzaib, Ahmadzade, Mohadese, Ahmed, Ali, Ahmed, Ayman ... Murray, Christopher J. L. (2024). Burden of disease scenarios by state in the USA, 2022-50: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet, 404 (10469), 2341-2370. doi: 10.1016/S0140-6736(24)02246-3
2024
Journal Article
Burden of disease scenarios by state in the USA, 2022-50: a forecasting analysis for the Global Burden of Disease Study 2021
Mokdad, Ali H., Bisignano, Catherine, Hsu, Johnathan M., Bryazka, Dana, Cao, Shujin, Bhattacharjee, Natalia V., Dalton, Bronte E., Lindstedt, Paulina A., Smith, Amanda E., Ababneh, Hazim S., Abbasgholizadeh, Rouzbeh, Abdelkader, Atef, Abdi, Parsa, Abiodun, Olugbenga Olusola, Aboagye, Richard Gyan, Abukhadijah, Hana J., Abu-Zaid, Ahmed, Acuna, Juan Manuel, Addo, Isaac Yeboah, Adekanmbi, Victor, Adeyeoluwa, Temitayo Esther, Adzigbli, Leticia Akua, Afolabi, Aanuoluwapo Adeyimika, Afrashteh, Fatemeh, Agyemang-Duah, Williams, Ahmad, Shahzaib, Ahmadzade, Mohadese, Ahmed, Ali, Ahmed, Ayman ... Murray, Christopher J. L. (2024). Burden of disease scenarios by state in the USA, 2022-50: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet, 404 (10469), 2341-2370.
2024
Journal Article
The burden of diseases, injuries, and risk factors by state in the USA, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Mokdad, Ali H, Bisignano, Catherine, Hsu, Johnathan M, Aldridge, Robert W, Aravkin, Aleksandr Y, Brauer, Michael, Bryazka, Dana, Cagney, Jack, Cogen, Rebecca M, Culbreth, Garland T, Dai, Xiaochen, Daoud, Farah, Degenhardt, Louisa, Dwyer-Lindgren, Laura, Feigin, Valery L, Flor, Luisa S, Fu, Weijia, Gardner, William M, Haakenstad, Annie, Haile, Demewoz, Hamilton, Erin B, Hay, Simon I, Ikuta, Kevin S, Kassebaum, Nicholas J, Lim, Stephen S, Mestrovic, Tomislav, Moberg, Madeline E, Mougin, Vincent, Naghavi, Mohsen ... Zyoud, Sa'ed H (2024). The burden of diseases, injuries, and risk factors by state in the USA, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 404 (10469), 2314-2340. doi: 10.1016/S0140-6736(24)01446-6
2024
Journal Article
Correction to: A computational approach to design a polyvalent vaccine against human respiratory syncytial virus (Scientific Reports, (2023), 13, 1, (9702), 10.1038/s41598-023-35309-y)
Moin, Abu Tayab, Ullah, Md. Asad, Patil, Rajesh B., Faruqui, Nairita Ahsan, Araf, Yusha, Das, Sowmen, Uddin, Khaza Md. Kapil, Hossain, Md. Shakhawat, Miah, Md. Faruque, Moni, Mohammad Ali, Chowdhury, Dil Umme Salma and Islam, Saiful (2024). Correction to: A computational approach to design a polyvalent vaccine against human respiratory syncytial virus (Scientific Reports, (2023), 13, 1, (9702), 10.1038/s41598-023-35309-y). Scientific Reports, 14 (1) 15721, 15721. doi: 10.1038/s41598-024-66721-7
2024
Journal Article
The global, regional, and national burden of urolithiasis in 204 countries and territories, 2000–2021: a systematic analysis for the Global Burden of Disease Study 2021
Awedew, Atalel Fentahun, Han, Hannah, Berice, Bétyna N., Dodge, Maxwell, Schneider, Rachel D., Abbasi-Kangevari, Mohsen, Al-Aly, Ziyad, Almidani, Omar, Alvand, Saba, Arabloo, Jalal, Aravkin, Aleksandr Y., Ayana, Tegegn Mulatu, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhaskar, Sonu, Bikbov, Boris, Caetano dos Santos, Florentino Luciano, Charan, Jaykaran, Cruz-Martins, Natalia, Dadras, Omid, Dai, Xiaochen, Digesa, Lankamo Ena, Elhadi, Muhammed, Elmonem, Mohamed A., Esezobor, Christopher Imokhuede, Fatehizadeh, Ali, Gebremeskel, Teferi Gebru, Getachew, Motuma Erena, Ghamari, Seyyed-Hadi ... GBD 2021 Urolithiasis Collaborators (2024). The global, regional, and national burden of urolithiasis in 204 countries and territories, 2000–2021: a systematic analysis for the Global Burden of Disease Study 2021. eClinicalMedicine, 78 102924, 1-29. doi: 10.1016/j.eclinm.2024.102924
2024
Journal Article
Global, regional, and national burden of HIV/AIDS, 1990–2021, and forecasts to 2050, for 204 countries and territories: the Global Burden of Disease Study 2021
Carter, Austin, Zhang, Meixin, Tram, Khai Hoan, Walters, Magdalene K, Jahagirdar, Deepa, Brewer, Edmond D, Novotney, Amanda, Lasher, Dylan, Mpolya, Emmanuel A, Vongpradith, Avina, Ma, Jianing, Verma, Megan, Frank, Tahvi D, He, Jiawei, Byrne, Sam, Lin, Christine, Dominguez, Regina-Mae Villanueva, Pease, Spencer A, Comfort, Haley, May, Erin A, Abate, Yohannes Habtegiorgis, Abbastabar, Hedayat, Abdelkader, Atef, Abdi, Parsa, Abdoun, Meriem, Abdul Aziz, Jeza Muhamad, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan ... GBD 2021 HIV Collaborators (2024). Global, regional, and national burden of HIV/AIDS, 1990–2021, and forecasts to 2050, for 204 countries and territories: the Global Burden of Disease Study 2021. The Lancet HIV, 11 (12), e807-e822. doi: 10.1016/s2352-3018(24)00212-1
2024
Journal Article
DeepQSP: identification of quorum sensing peptides through neural network model
Ashikur Rahman, Md., Mamun Ali, Md., Ahmed, Kawsar, Mahmud, Imran, Bui, Francis M., Chen, Li, Kumar, Santosh and Moni, Mohammad Ali (2024). DeepQSP: identification of quorum sensing peptides through neural network model. Results in Engineering, 24 102878, 102878. doi: 10.1016/j.rineng.2024.102878
2024
Journal Article
Prediction of white blood cell count during exercise: a comparison between standalone and hybrid intelligent algorithms
Asadi, Shirin, Tartibian, Bakhtyar, Moni, Mohammad Ali and Eslami, Rasoul (2024). Prediction of white blood cell count during exercise: a comparison between standalone and hybrid intelligent algorithms. Scientific Reports, 14 (1) 20683. doi: 10.1038/s41598-024-71576-z
2024
Journal Article
An integrated framework to identify prognostic biomarkers and novel therapeutic targets in hepatocellular carcinoma-based disabilities
Rahman, Md. Okibur, Das, Asim, Naeem, Nazratun, Jabeen-E-Tahnim,, Hossain, Md. Ali, Alam, Md. Nur, Azad, A. K. M., Alyami, Salem A., Alotaibi, Naif, Al-Moisheer, A. S. and Moni, Mohammod Ali (2024). An integrated framework to identify prognostic biomarkers and novel therapeutic targets in hepatocellular carcinoma-based disabilities. Biology, 13 (12) 966, 966. doi: 10.3390/biology13120966
2024
Journal Article
A novel mixed convolution transformer model for the fast and accurate diagnosis of glioma subtypes
Nobel, S. M. Nuruzzaman, Swapno, S. M. Masfequier Rahman, Islam, Md Babul, Azad, AKM, Alyami, Salem A., Alamin, Md, Liò, Pietro and Moni, Mohammad Ali (2024). A novel mixed convolution transformer model for the fast and accurate diagnosis of glioma subtypes. Advanced Intelligent Systems, 7 (5) 2400566. doi: 10.1002/aisy.202400566
2024
Conference Publication
Real-Time Human Activity Recognition Using Non-intrusive Sensing and Continual Learning
Rahman, Md Geaur, ur Rehman, Sabih, Fealy, Shanna, Vallejo, Johan Sebastian Ramirez, Fuskelay, Aayush and Moni, Mohammad Ali (2024). Real-Time Human Activity Recognition Using Non-intrusive Sensing and Continual Learning. 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC Australia, 25–29 November 2024. Singapore: Springer. doi: 10.1007/978-981-96-0351-0_30
2024
Journal Article
LandSin: a differential ML and google API-enabled web server for real-time land insights and beyond
Sabari, Alauddin, Hasan, Imran, Alyami, Salem A., Liò, Pietro, Ali, Md. Sadek, Moni, Mohammad Ali and Azad, AKM (2024). LandSin: a differential ML and google API-enabled web server for real-time land insights and beyond. Software Impacts, 22 100718, 1-6. doi: 10.1016/j.simpa.2024.100718
Supervision
Availability
- Dr Mohammad Ali Moni is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose 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
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
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
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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