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
2022
Journal Article
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins
Hosen, Md. Faruk, Mahmud, S.M. Hasan, Ahmed, Kawsar, Chen, Wenyu, Moni, Mohammad Ali, Deng, Hong-Wen, Shoombuatong, Watshara and Hasan, Md Mehedi (2022). DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins. Computers in Biology and Medicine, 145 105433, 1-12. doi: 10.1016/j.compbiomed.2022.105433
2022
Journal Article
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides
Charoenkwan, Phasit, Schaduangrat, Nalini, Lio, Pietro, Moni, Mohammad Ali, Manavalan, Balachandran and Shoombuatong, Watshara (2022). NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Computers in Biology and Medicine, 148 105700, 1-10. doi: 10.1016/j.compbiomed.2022.105700
2022
Journal Article
Metals in e-waste: occurrence, fate, impacts and remediation technologies
Chakraborty, S. C., Qamruzzaman, M., Zaman, M. W.U., Alam, Md Masruck, Hossain, Md Delowar, Pramanik, B. K., Nguyen, L. N., Nghiem, L. D., Ahmed, M. F., Zhou, J. L., Mondal, Md. Ibrahim.H., Hossain, M. A., Johir, M. A.H., Ahmed, M. B., Sithi, J. A., Zargar, M. and Moni, Mohammad Ali (2022). Metals in e-waste: occurrence, fate, impacts and remediation technologies. Process Safety and Environmental Protection, 162, 230-252. doi: 10.1016/j.psep.2022.04.011
2022
Journal Article
MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients
Mehedi, Sk. Tanzir, Ahmed, Kawsar, Bui, Francis M, Rahaman, Musfikur, Hossain, Imran, Tonmoy, Tareq Mahmud, Limon, Rakibul Alam, Ibrahim, Sobhy M and Moni, Mohammad Ali (2022). MLBioIGE: integration and interplay of machine learning and bioinformatics approach to identify the genetic effect of SARS-COV-2 on idiopathic pulmonary fibrosis patients. Biology Methods and Protocols, 7 (1) bpac013, 1-17. doi: 10.1093/biomethods/bpac013
2022
Journal Article
Mutual Interdependence of the physical parameters governing the boundary-layer flow of non-Newtonian fluids
Al-Ashhab, Samer, Wei, Dongming, Alyami, Salem A., Azad, AKM and Moni, Mohammad Ali (2022). Mutual Interdependence of the physical parameters governing the boundary-layer flow of non-Newtonian fluids. Applied Sciences, 12 (10) 5275, 1-12. doi: 10.3390/app12105275
2022
Journal Article
Efficient machine learning models for early stage detection of autism spectrum disorder
Bala, Mousumi, Ali, Mohammad Hanif, Satu, Md. Shahriare, Hasan, Khondokar Fida and Moni, Mohammad Ali (2022). Efficient machine learning models for early stage detection of autism spectrum disorder. Algorithms, 15 (5) 166, 166. doi: 10.3390/a15050166
2022
Journal Article
Discovering common pathophysiological processes between COVID-19 and cystic fibrosis by differential gene expression pattern analysis
Hasan, Md. Tanvir, Abdulrazak, Lway Faisal, Alam, Mohammad Khursheed, Islam, Md. Rezwan, Sathi, Yeasmin Hena, Al-Zahrani, Fahad Ahmed, Ahmed, Kawsar, Bui, Francis M. and Moni, Mohammad Ali (2022). Discovering common pathophysiological processes between COVID-19 and cystic fibrosis by differential gene expression pattern analysis. BioMed Research International, 2022 (1) 8078259, 8078259. doi: 10.1155/2022/8078259
2022
Journal Article
Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction
Uddin, Shahadat, Haque, Ibtisham, Lu, Haohui, Moni, Mohammad Ali and Gide, Ergun (2022). Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction. Scientific Reports, 12 (1) 6256, 6256. doi: 10.1038/s41598-022-10358-x
2022
Journal Article
Different types of screen time are associated with low life satisfaction in adolescents across 37 European and North American countries
Khan, Asaduzzaman, Moni, Mohammad A., Khan, Shanchita R. and Burton, Nicola W. (2022). Different types of screen time are associated with low life satisfaction in adolescents across 37 European and North American countries. Scandinavian Journal of Public Health, 51 (6) 14034948221082459, 140349482210824-925. doi: 10.1177/14034948221082459
2022
Journal Article
A machine learning model for predicting individual substance abuse with associated risk-factors
Islam, Uwaise Ibna, Haque, Enamul, Alsalman, Dheyaaldin, Islam, Muhammad Nazrul, Moni, Mohammad Ali and Sarker, Iqbal H. (2022). A machine learning model for predicting individual substance abuse with associated risk-factors. Annals of Data Science, 10 (6), 1-28. doi: 10.1007/s40745-022-00381-0
2022
Conference Publication
Predictive risk modelling in mental health issues using machine learning on graphs
Lu, Haohui, Uddin, Shahadat, Hajati, Farshid, Khushi, Matloob and Moni, Mohammad Ali (2022). Predictive risk modelling in mental health issues using machine learning on graphs. ACSW 2022: Australasian Computer Science Week 2022, Online, 14 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3511616.3513112
2022
Conference Publication
Early stage autism spectrum disorder detection of adults and toddlers using machine learning models
Hasan, Minhazul, Ahamad, Md. Martuza, Aktar, Sakifa and Moni, Mohammad Ali (2022). Early stage autism spectrum disorder detection of adults and toddlers using machine learning models. 2021 5th International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh, 17-19 December 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/EICT54103.2021.9733664
2022
Conference Publication
A machine learning model to recognise human emotions using electroencephalogram
Roy, Nipa, Aktar, Sakifa, Ahamad, Md. Martuza and Moni, Mohammad Ali (2022). A machine learning model to recognise human emotions using electroencephalogram. 2021 5th International Conference on Electrical Information and Communication Technology (EICT), Khulna, Bangladesh, 17-19 December 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/EICT54103.2021.9733675
2022
Journal Article
SCORPION is a stacking-based ensemble learning framework for accurate prediction of phage virion proteins
Ahmad, Saeed, Charoenkwan, Phasit, Quinn, Julian M. W., Moni, Mohammad Ali, Hasan, Md Mehedi, Lio', Pietro and Shoombuatong, Watshara (2022). SCORPION is a stacking-based ensemble learning framework for accurate prediction of phage virion proteins. Scientific Reports, 12 (1) 4106, 1-15. doi: 10.1038/s41598-022-08173-5
2022
Journal Article
Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019
Cousin, Ewerton, Duncan, Bruce B., Stein, Caroline, Ong, Kanyin Liane, Vos, Theo, Abbafati, Cristiana, Abbasi-Kangevari, Mohsen, Abdelmasseh, Michael, Abdoli, Amir, Abd-Rabu, Rami, Abolhassani, Hassan, Abu-Gharbieh, Eman, Accrombessi, Manfred Mario Kokou, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Muhammad Sohail, Agarwal, Gina, Agrawaal, Krishna K., Agudelo-Botero, Marcela, Ahinkorah, Bright Opoku, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadi, Sepideh, Ahmadi, Ali, Ahmed, Ali, Salih, Yusra Ahmed, Akande-Sholabi, Wuraola, Akram, Tayyaba, Al Hamad, Hanadi ... Schmidt, Maria Ines (2022). Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019. Lancet Diabetes and Endocrinology, 10 (3), 177-192. doi: 10.1016/S2213-8587(21)00349-1
2022
Journal Article
Machine learning models for classification and identification of significant attributes to detect type 2 diabetes
Howlader, Koushik Chandra, Satu, Md. Shahriare, Awal, Md. Abdul, Islam, Md. Rabiul, Islam, Sheikh Mohammed Shariful, Quinn, Julian M. W. and Moni, Mohammad Ali (2022). Machine learning models for classification and identification of significant attributes to detect type 2 diabetes. Health Information Science and Systems, 10 (1) 2, 2. doi: 10.1007/s13755-021-00168-2
2022
Journal Article
Network based systems biology approach to identify diseasome and comorbidity associations of Systemic Sclerosis with cancers
Islam, Md Khairul, Rahman, Md. Habibur, Islam, Md Rakibul, Islam, Md Zahidul, Mamun, Md Mainul Islam, Azad, A. K.M. and Moni, Mohammad Ali (2022). Network based systems biology approach to identify diseasome and comorbidity associations of Systemic Sclerosis with cancers. Heliyon, 8 (2) e08892, e08892. doi: 10.1016/j.heliyon.2022.e08892
2022
Journal Article
A patient network-based machine learning model for disease prediction: The case of type 2 diabetes mellitus
Lu, Haohui, Uddin, Shahadat, Hajati, Farshid, Moni, Mohammad Ali and Khushi, Matloob (2022). A patient network-based machine learning model for disease prediction: The case of type 2 diabetes mellitus. Applied Intelligence, 52 (3), 2411-2422. doi: 10.1007/s10489-021-02533-w
2022
Journal Article
Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990–2019: results from the Global Burden of Disease Study 2019
Ledesma, Jorge R, Ma, Jianing, Vongpradith, Avina, Maddison, Emilie R, Novotney, Amanda, Biehl, Molly H, LeGrand, Kate E, Ross, Jennifer M, Jahagirdar, Deepa, Bryazka, Dana, Feldman, Rachel, Abolhassani, Hassan, Abosetugn, Akine Eshete, Abu-Gharbieh, Eman, Adebayo, Oladimeji M, Adnani, Qorinah Estiningtyas Sakilah, Afzal, Saira, Ahinkorah, Bright Opoku, Ahmad, Sajjad Ahmad, Ahmadi, Sepideh, Ahmed Rashid, Tarik, Ahmed Salih, Yusra, Aklilu, Addis, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alahdab, Fares, Alemayehu, Yosef, Alene, Kefyalew Addis, Ali, Beriwan Abdulqadir ... Kyu, Hmwe Hmwe (2022). Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990–2019: results from the Global Burden of Disease Study 2019. The Lancet Infectious Diseases, 22 (2), 222-241. doi: 10.1016/S1473-3099(21)00449-7
2022
Journal Article
Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019
GBD 2019 Dementia Forecasting Collaborators, Moniruzzaman, Md and Moni, Mohammad Ali (2022). Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. The Lancet. Public health, 7 (2), e105-e125. doi: 10.1016/S2468-2667(21)00249-8
Supervision
Availability
- Dr Mohammad Ali Moni is:
- Available for supervision
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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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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
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
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
Enquiries
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