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
2023
Conference Publication
What baseline and intervention characteristics predict walking speed six months after stroke?
Nayak, Neelam, Brauer, Sandra, Kuys, Suzanne, Moni, Mohammad Ali and Mahendran, Niruthikha (2023). What baseline and intervention characteristics predict walking speed six months after stroke?. Stroke 2023 – The Combined Stroke Society of Australasia and Smart Strokes Nursing and Allied Health Scientific Meeting, Melbourne, VIC, Australia, 22-25 August 2023. London, United Kingdom: Sage Publications.
2023
Journal Article
Global, regional, and national burden of meningitis and its aetiologies, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019
Wunrow, Han Yong, Bender, Rose G., Vongpradith, Avina, Sirota, Sarah Brooke, Swetschinski, Lucien R., Novotney, Amanda, Gray, Authia P., Ikuta, Kevin S., Sharara, Fablina, Wool, Eve E., Aali, Amirali, Abd-Elsalam, Sherief, Abdollahi, Ashkan, Aziz, Jeza Muhamad Abdul, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Abu-Gharbieh, Eman, Adamu, Lawan Hassan, Adane, Tigist Demssew, Addo, Isaac Yeboah, Adegboye, Oyelola A., Adekiya, Tayo Alex, Adnan, Mohammad, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Saira, Aghamiri, Shahin, Aghdam, Zahra Babaei, Agodi, Antonella ... Kyu, Hmwe Hmwe (2023). Global, regional, and national burden of meningitis and its aetiologies, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurology, 22 (8), 685-711.
2023
Journal Article
Integrated bioinformatics and statistical approach to identify the cmmon mlecular mchanisms of oesity that are linked to the development of two psychiatric disorders: Schizophrenia and major depressive disorder
Islam, Md Khairul, Islam, Md Rakibul, Rahman, Md Habibur, Islam, Md Zahidul, Hasan, Md Mehedi, Mamun, Md Mainul Islam and Moni, Mohammad Ali (2023). Integrated bioinformatics and statistical approach to identify the cmmon mlecular mchanisms of oesity that are linked to the development of two psychiatric disorders: Schizophrenia and major depressive disorder. PLOS ONE, 18 (7) e0276820, e0276820. doi: 10.1371/journal.pone.0276820
2023
Journal Article
A comparison of machine learning techniques for the detection of type-2 diabetes mellitus: experiences from Bangladesh
Uddin, Md. Jamal, Ahamad, Md. Martuza, Hoque, Md. Nesarul, Walid, Md. Abul Ala, Aktar, Sakifa, Alotaibi, Naif, Alyami, Salem A., Kabir, Muhammad Ashad and Moni, Mohammad Ali (2023). A comparison of machine learning techniques for the detection of type-2 diabetes mellitus: experiences from Bangladesh. Information, 14 (7) 376, 376. doi: 10.3390/info14070376
2023
Journal Article
An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis
Bristy, Sadia Afrin, Hossain, Md Arju, Hasan, Md Imran, Mahmud, S M Hasan, Moni, Mohammad Ali and Rahman, Md Habibur (2023). An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis. Briefings in Functional Genomics, 22 (4), 375-391. doi: 10.1093/bfgp/elad005
2023
Journal Article
Ensemble learning for disease prediction: a review
Mahajan, Palak, Uddin, Shahadat, Hajati, Farshid and Moni, Mohammad Ali (2023). Ensemble learning for disease prediction: a review. Healthcare, 11 (12) 1808. doi: 10.3390/healthcare11121808
2023
Journal Article
A novel hybrid approach for classifying osteosarcoma using deep feature extraction and multilayer perceptron
Aziz, Md. Tarek, Mahmud, S. M. Hasan, Elahe, Md. Fazla, Jahan, Hosney, Rahman, Md Habibur, Nandi, Dip, Smirani, Lassaad K., Ahmed, Kawsar, Bui, Francis M. and Moni, Mohammad Ali (2023). A novel hybrid approach for classifying osteosarcoma using deep feature extraction and multilayer perceptron. Diagnostics, 13 (12) 2106, 2106. doi: 10.3390/diagnostics13122106
2023
Conference Publication
Machine learning-based biomedical antenna for brain tumor detection
Hasan, Nafiul, Aktar, Mousumi, Rana, Md. Masud and Moni, Mohammad Ali (2023). Machine learning-based biomedical antenna for brain tumor detection. International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM), Gazipur, Bangladesh, 16-17 June 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/ncim59001.2023.10212805
2023
Book Chapter
A dynamic topic identification and labeling approach for COVID-19 tweets
Shahriar, Khandaker Tayef, Islam, Muhammad Nazrul, Moni, Mohammad Ali and Sarker, Iqbal H. (2023). A dynamic topic identification and labeling approach for COVID-19 tweets. Applied Intelligence for Industry 4.0. (pp. 227-239) edited by Nazmul Siddique, Mohammad Shamsul Arefin, M. Shamim Kaiser and A.S.M. Kayes. New York, NY United States: CRC Press. doi: 10.1201/9781003256083-18
2023
Journal Article
The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells
Hossain, Md. Ali, Asa, Tania Akter, Auwul, Md. Rabiul, Aktaruzzaman, Md., Rahman, Md. Mahfizur and Moni, Mohammad Ali (2023). The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells. Computers in Biology and Medicine, 159 106885, 1-8. doi: 10.1016/j.compbiomed.2023.106885
2023
Journal Article
Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021
Ferreira, Manuela L, de Luca, Katie, Haile, Lydia M, Steinmetz, Jaimie D, Culbreth, Garland T, Cross, Marita, Kopec, Jacek A, Ferreira, Paulo H, Blyth, Fiona M, Buchbinder, Rachelle, Hartvigsen, Jan, Wu, Ai-Min, Safiri, Saeid, Woolf, Anthony D, Collins, Gary S, Ong, Kanyin Liane, Vollset, Stein Emil, Smith, Amanda E, Cruz, Jessica A, Fukutaki, Kai Glenn, Abate, Semagn Mekonnen, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdelalim, Ahmed, Abedi, Aidin, Abidi, Hassan, Adnani, Qorinah Estiningtyas Sakilah, Ahmadi, Ali ... March, Lyn M (2023). Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. The Lancet Rheumatology, 5 (6), e316-e329. doi: 10.1016/s2665-9913(23)00098-x
2023
Journal Article
Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021
Ferreira, Manuela L., de Luca, Katie, Haile, Lydia M., Steinmetz, Jaimie, Culbreth, Garland, Cross, Marita, Kopec, Jacek A., Ferreira, Paulo H., Blyth, Fiona M., Buchbinder, Rachelle, Hartvigsen, Jan, Wu, Ai-Min, Safiri, Saeid, Woolf, Anthony, Collins, Gary S., Ong, Kanyin Liane, Vollset, Stein Emil, Smith, Amanda E., Cruz, Jessica A., Fukutaki, Kai Glenn, Abate, Semagn Mekonnen, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdelalim, Ahmed, Abedi, Aidin, Abidi, Hassan, Adnani, Qorinah Estiningtyas Sakilah, Ahmadi, Ali ... March, Lyn M. (2023). Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. Lancet Rheumatology, 5 (6), E316-E329.
2023
Journal Article
Machine learning-based model to predict heart disease in early stage employing different feature selection techniques
Biswas, Niloy, Ali, Md Mamun, Rahaman, Md Abdur, Islam, Minhajul, Mia, Md. Rajib, Azam, Sami, Ahmed, Kawsar, Bui, Francis M., Al-Zahrani, Fahad Ahmed and Moni, Mohammad Ali (2023). Machine learning-based model to predict heart disease in early stage employing different feature selection techniques. BioMed Research International, 2023 (1) 6864343, 1-15. doi: 10.1155/2023/6864343
2023
Journal Article
HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN
Islam, Md Shofiqul, Hasan, Khondokar Fida, Sultana, Sunjida, Uddin, Shahadat, Lio’, Pietro, Quinn, Julian M.W. and Moni, Mohammad Ali (2023). HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. Neural Networks, 162, 271-287. doi: 10.1016/j.neunet.2023.03.004
2023
Journal Article
Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019
Momtazmanesh, Sara, Moghaddam, Sahar Saeedi, Ghamari, Seyyed-Hadi, Rad, Elaheh Malakan, Rezaei, Negar, Shobeiri, Parnian, Aali, Amirali, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdelmasseh, Michael, Abdoun, Meriem, Abdulah, Deldar Morad, Md Abdullah, Abu Yousuf, Abedi, Aidin, Abolhassani, Hassan, Abrehdari-Tafreshi, Zahra, Achappa, Basavaprabhu, Adane Adane, Denberu Eshetie, Adane, Tigist Demssew, Addo, Isaac Yeboah, Adnan, Mohammad, Sakilah Adnani, Qorinah Estiningtyas, Ahmad, Sajjad, Ahmadi, Ali, Ahmadi, Keivan, Ahmed, Ali, Ahmed, Ayman, Rashid, Tarik Ahmed, Al Hamad, Hanadi ... GBD 2019 Chronic Respiratory Diseases Collaborators (2023). Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019. eClinicalMedicine, 59 101936, 101936. doi: 10.1016/j.eclinm.2023.101936
2023
Journal Article
Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke
Islam, Tania, Rahman, Md Rezanur, Khan, Asaduzzaman and Moni, Mohammad Ali (2023). Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke. Journal of Biomedical Informatics, 141 104345, 1-13. doi: 10.1016/j.jbi.2023.104345
2023
Journal Article
An integrated statistical and clinically applicable machine learning framework for the detection of autism spectrum disorder
Uddin, Md. Jamal, Ahamad, Md. Martuza, Sarker, Prodip Kumar, Aktar, Sakifa, Alotaibi, Naif, Alyami, Salem A., Kabir, Muhammad Ashad and Moni, Mohammad Ali (2023). An integrated statistical and clinically applicable machine learning framework for the detection of autism spectrum disorder. Computers, 12 (5) 92, 1-19. doi: 10.3390/computers12050092
2023
Journal Article
GRU-INC: an inception-attention based approach using GRU for human activity recognition
Mim, Taima Rahman, Amatullah, Maliha, Afreen, Sadia, Yousuf, Mohammad Abu, Uddin, Shahadat, Alyami, Salem A., Hasan, Khondokar Fida and Moni, Mohammad Ali (2023). GRU-INC: an inception-attention based approach using GRU for human activity recognition. Expert Systems with Applications, 216 119419, 119419. doi: 10.1016/j.eswa.2022.119419
2023
Journal Article
Multi-omics data integration methods and their applications in psychiatric disorders
Sathyanarayanan, Anita, Mueller, Tamara T., Ali Moni, Mohammad, Schueler, Katja, Baune, Bernhard T., Lio, Pietro, Mehta, Divya, Baune, Bernhard T, Dierssen, Mara, Ebert, Bjarke, Fabbri, Chiara, Fusar-Poli, Paolo, Gennarelli, Massimo, Harmer, Catherine, Howes, Oliver D., Janzing, Joost G.E., Lio, Pietro, Maron, Eduard, Mehta, Divya, Minelli, Alessandra, Nonell, Lara, Pisanu, Claudia, Potier, Marie-Claude, Rybakowski, Filip, Serretti, Alessandro, Sqassina, Alessio, Stacey, David, van Westrhenen, Roos and Xicota, Laura (2023). Multi-omics data integration methods and their applications in psychiatric disorders. European Neuropsychopharmacology, 69, 26-46. doi: 10.1016/j.euroneuro.2023.01.001
2023
Journal Article
An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients
Hossain, Md Arju, Rahman, Md Habibur, Sultana, Habiba, Ahsan, Asif, Rayhan, Saiful Islam, Hasan, Md Imran, Sohel, Md, Somadder, Pratul Dipta and Moni, Mohammad Ali (2023). An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients. Computers in Biology and Medicine, 155 106656, 1-21. doi: 10.1016/j.compbiomed.2023.106656
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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Master Philosophy
Advancing Maternal-Fetal Health in Underserved Communities: A Computer Vision Approach
Principal Advisor
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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
Understanding the pathophysiology of stroke using bioinformatics and statistical genetics
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan, Dr Jian Zeng
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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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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
Understanding the pathophysiology of stroke using bioinformatics and statistical genetics approaches
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan, Dr Jian Zeng
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Doctor Philosophy
Understanding the pathophysiology of stroke using bioinformatics and statistical genetics
Principal Advisor
Other advisors: Associate Professor Asaduzzaman Khan, Dr Jian Zeng
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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
Media
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