Dr Mohammad Ali Moni
Dr

Mohammad Ali Moni

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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

Applications in life sciences Applied computing Artificial intelligence Biological Sciences Biomedical and Clinical Sciences Biomedical engineering Cardiovascular medicine and haematology Clinical sciences Cognitive and computational psychology Computer vision and multimedia computation Cybersecurity and privacy Data management and data science Distributed computing and systems software Engineering Health Sciences Human-centred computing Information and Computing Sciences Informetrics Library and information studies Machine learning Medical biotechnology Mobile computing Nanotechnology Neurosciences Other engineering Psychology Sports science and exercise

Qualifications

  • Doctor of Philosophy, University of Cambridge

Research interests

  • Artificial Intelligence, Computer Vision, Machine Learning, Deep-Learning

  • Medical Imaging, Medical Image Analysis, Neuro Imaging

  • Digital Health, Data Science, Health Informatics, Clinical Informatics

  • Data Mining, Text Mining, Natural Language Processing

  • 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

Search Professor Mohammad Ali Moni’s works on UQ eSpace

416 works between 2012 and 2026
All (416) Book (2) Journal Article (355) Conference Publication (53) Book Chapter (6)

1 - 20 of 416 works

2026

Journal Article

An explainable deep learning model for mulberry leaf classification and disease detection

Nobel, S.M. Nuruzzaman, Tasir, Md All Moon, Sultana, Shirin, Al-Moisheer, Asmaa Soliman and Moni, Mohammad Ali (2026). An explainable deep learning model for mulberry leaf classification and disease detection. Engineering Applications of Artificial Intelligence, 165 113470, 113470. doi: 10.1016/j.engappai.2025.113470

An explainable deep learning model for mulberry leaf classification and disease detection

2026

Journal Article

Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics

Asa, Tania Akter, Hossain, Md Ali, Ali, Md Shahjahan, Mahmud, Md Zulfiker, Azad, A K M, Rahman, Mohammad Zahidur and Moni, Mohammad Ali (2026). Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics. Briefings in Functional Genomics, 25 elaf019. doi: 10.1093/bfgp/elaf019

Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics

2026

Journal Article

StackAPP: Advancing autophagy protein identification with ensemble learning

Shoyshob, Munem Shahriar, Al-Tabatabaie, Kusay Faisal, Abdulrazak, Lway Faisal, Rahman, Md. Ashikur, Ali, Md. Mamun, Ibrahim, Sobhy M., Ahmed, Kawsar, Bui, Francis M. and Moni, Mohammad Ali (2026). StackAPP: Advancing autophagy protein identification with ensemble learning. Analytical Biochemistry, 708 115981, 115981-708. doi: 10.1016/j.ab.2025.115981

StackAPP: Advancing autophagy protein identification with ensemble learning

2026

Journal Article

RGNN3D: A Hybrid Radiomic Graph Neural Network for 3D MRI Glioma Grading

Ali, Md Aiyub, Hossain, Md Shakhawat, Shuva, Taslima Ferdaus, Almoyad, Muhammad Ali Abdullah, Orka, Nabil Anan, Khan, Risala Tasin, Kaiser, M. Shamim, Rahman, Md Tanvir and Moni, Mohammad Ali (2026). RGNN3D: A Hybrid Radiomic Graph Neural Network for 3D MRI Glioma Grading. Knowledge-Based Systems 115343, 115343. doi: 10.1016/j.knosys.2026.115343

RGNN3D: A Hybrid Radiomic Graph Neural Network for 3D MRI Glioma Grading

2026

Journal Article

Deep3BPP: identification of blood-brain barrier penetrating peptides using word embedding feature extraction method and CNN-LSTM

Rahman, Md. Ashikur, Ali, Md Mamun, Ahmed, Kawsar, Mahmud, Imran, Bui, Francis M., Chen, Li and Moni, Mohammad Ali (2026). Deep3BPP: identification of blood-brain barrier penetrating peptides using word embedding feature extraction method and CNN-LSTM. IEEE Transactions on Artificial Intelligence, 7 (1), 562-570. doi: 10.1109/tai.2025.3567434

Deep3BPP: identification of blood-brain barrier penetrating peptides using word embedding feature extraction method and CNN-LSTM

2026

Journal Article

Quantifying the fatal and non-fatal burden of disease associated with child growth failure, 2000–2023: a systematic analysis from the Global Burden of Disease Study 2023

Troeger, Christopher E, Arndt, Michael Benjamin, Aalruz, Hasan, Abdoun, Meriem, Abdullahi, Auwal, Abebe, Mesfin, Abedi, Armita, Abie, Alemwork, Aboagye, Richard Gyan, Abolhassani, Hassan, Abtew, Yonas Derso, Abu-Zaid, Ahmed, Adamu, Lawan Hassan, Adane, Mesafint Molla, Addo, Isaac Yeboah, Adegboye, Oyelola A, Adekanmbi, Victor, Adetunji, Juliana Bunmi, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afzal, Muhammad Sohail, Afzal, Saira, Aggarwal, Navidha, Ahmad, Aqeel, Ahmad, Muayyad M, Ahmad, Sajjad, Ahmadi, Elham, Ahmed, Ayman, Ahmed, Haroon ... Reiner, Robert C (2026). Quantifying the fatal and non-fatal burden of disease associated with child growth failure, 2000–2023: a systematic analysis from the Global Burden of Disease Study 2023. The Lancet Child & Adolescent Health, 10 (1), 22-38. doi: 10.1016/s2352-4642(25)00303-7

Quantifying the fatal and non-fatal burden of disease associated with child growth failure, 2000–2023: a systematic analysis from the Global Burden of Disease Study 2023

2026

Journal Article

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features

Hasan, Md. Zahid, Shakil, Md. Shahriar, Karim, Tasmin, Shaon, Md. Shazzad Hossain, Sultan, Md. Fahim, Rupa, Fatema Hashem, Almoyad, Muhammad Ali Abdullah, Rahman, Md. Tanvir, Khan, Risala Tasin, Kaiser, M. Shamim and Moni, Mohammad Ali (2026). A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features. IEEE Transactions on Computational Biology and Bioinformatics, 1-14. doi: 10.1109/tcbbio.2026.3654071

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features

2025

Journal Article

Prevention and Management of Heart Failure Associated with Type 2 Diabetics in Rural Australia

Ross, Allen G., Mondal, Utpal K., Mahmood, Shakeel, Astawesegn, Feleke H., Anyasodor, Anayochukwu E., Huda, M. Mamun, Thapa, Subash, Aychiluhm, Setognal B., Giri, Santosh, Rahman, Md. Ferdous, Shiddiky, Muhammad J. A., Moni, Mohammad Ali and Ahmed, Kedir Y. (2025). Prevention and Management of Heart Failure Associated with Type 2 Diabetics in Rural Australia. Journal of Clinical Medicine, 15 (1) 304, 304. doi: 10.3390/jcm15010304

Prevention and Management of Heart Failure Associated with Type 2 Diabetics in Rural Australia

2025

Journal Article

Correction: Digital Health for Australia: Bridging the Rural, Regional, and Remote Health Gap

Mahmood, Shakeel, Huda, M Mamun, Ahmed, Kedir Yimam, Subash, Thapa, Astawesegn, Feleke Hailemichael, Anyasodor, Anayochukwu Edward, Moni, Mohammad Ali, Shiddiky, Muhammad J A, Mondal, Utpal K, Aychiluhm, Setognal Birara, Giri, Santosh and Ross, Allen G (2025). Correction: Digital Health for Australia: Bridging the Rural, Regional, and Remote Health Gap. Interactive Journal of Medical Research, 14, e89755. doi: 10.2196/89755

Correction: Digital Health for Australia: Bridging the Rural, Regional, and Remote Health Gap

2025

Journal Article

ADeepWeeD: An adaptive deep learning framework for weed species classification

Rahman, Md Geaur, Rahman, Md Anisur, Parvez, Mohammad Zavid, Patwary, Md Anwarul Kaium, Ahamed, Tofael, Fleming-Muñoz, David A., Aloteibi, Saad and Moni, Mohammad Ali (2025). ADeepWeeD: An adaptive deep learning framework for weed species classification. Artificial Intelligence in Agriculture, 15 (4), 590-609. doi: 10.1016/j.aiia.2025.04.009

ADeepWeeD: An adaptive deep learning framework for weed species classification

2025

Journal Article

Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

Zuniga, Yves Miel H., Zumla, Alimuddin, Zuhlke, Liesl J., Zoladl, Mohammad, Ziaeian, Boback, Zhong, Chenwen, Zhao, Xiu-Ju George, Zhang, Zhi-Jiang, Zhang, Jianrong, Zepro, Nejimu Biza, Zenebe, Getachew Assefa, Zeitoun, Jean-David, Zegeye, Zelalem Banjaw, Zastrozhin, Mikhail Sergeevich, Zareshahrabadi, Zahra, Zarea, Kourosh, Dehnavi, Ali Zare, Zare, Iman, Zangiabadian, Moein, Zangeneh, Alireza, Zamora, Nelson, Zaman, Sojib Bin, Zaki, Nazar, Zakaryaei, Farima, Zahir, Mazyar, Tajrishi, Farbod Zahedi, Zadnik, Vesna, Zadey, Siddhesh, Yusefi, Hossein ... Anza-Ramirez, Cecilia (2025). Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019. Nature Communications, 16 (1) 4235, 1. doi: 10.1038/s41467-025-56910-x

Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

2025

Journal Article

K-SNOpred: identification of protein S-nitrosylation sites through word embedding features and machine learning

Karim, Tasmin, Shaon, Md. Shazzad Hossain, Ali, Md. Mamun, Ibrahim, Sobhy M., Akter, Mst Shapna, Ahmed, Kawsar, Bui, Francis M., Chen, Li and Moni, Mohammad Ali (2025). K-SNOpred: identification of protein S-nitrosylation sites through word embedding features and machine learning. Analytical Biochemistry, 707 115952, 115952-707. doi: 10.1016/j.ab.2025.115952

K-SNOpred: identification of protein S-nitrosylation sites through word embedding features and machine learning

2025

Journal Article

Global, regional, and national sepsis incidence and mortality, 1990–2021: a systematic analysis

Gray, Authia P, Chung, Erin, Hsu, Rebecca L, Araki, Daniel T, Gershberg Hayoon, Anna, Davis Weaver, Nicole, Swetschinski, Lucien R, Wool, Eve E, Han, Chieh, Mestrovic, Tomislav, Ikuta, Kevin S, Abbas, Nasir, Abbasi, Madineh, Abd ElHafeez, Samar, Abdisa, Wakgari Mosisa, Abdoun, Meriem, Abdullahi, Auwal, Abebe, Mesfin, Abejew, Asrat Agalu, Abie, Alemwork, Abolhassani, Hassan, Abukhadijah, Hana J, Achore, Meshack, Adams, Lisa C, Adedokun, Kamoru Ademola, Adesola, Ridwan Olamilekan, Adiga, Usha, Adnani, Qorinah Estiningtyas Sakilah, Afolabi, Aanuoluwapo Adeyimika ... Naghavi, Mohsen (2025). Global, regional, and national sepsis incidence and mortality, 1990–2021: a systematic analysis. The Lancet Global Health, 13 (12), e2013-e2026. doi: 10.1016/s2214-109x(25)00356-0

Global, regional, and national sepsis incidence and mortality, 1990–2021: a systematic analysis

2025

Journal Article

A vision transformer-based hybrid neural architecture for automated handwritten Bangla character recognition and braille conversion

Ahmed, Touseef Saleh Bin, Rahman, Tawhidur, Biswas, Shammo, Sabuj, Saifur Rahman, Bhuian, Mohammed Belal, Moni, Mohammad Ali and Alam, Md Ashraful (2025). A vision transformer-based hybrid neural architecture for automated handwritten Bangla character recognition and braille conversion. Knowledge-Based Systems, 330 114546, 114546. doi: 10.1016/j.knosys.2025.114546

A vision transformer-based hybrid neural architecture for automated handwritten Bangla character recognition and braille conversion

2025

Journal Article

Global, regional, and national burden of chronic kidney disease in adults, 1990-2023, and its attributable risk factors: a systematic analysis for the Global Burden of Disease Study 2023

GBD 2023 Chronic Kidney Disease Collaborators, Kanmiki, Edmund Wedam ( GBD 2023 Chronic Kidney Disease Collaborators member), Moni, Mohammad Ali ( GBD 2023 Chronic Kidney Disease Collaborators member) and Tesfaye, Wubshet H. ( GBD 2023 Chronic Kidney Disease Collaborators member) (2025). Global, regional, and national burden of chronic kidney disease in adults, 1990-2023, and its attributable risk factors: a systematic analysis for the Global Burden of Disease Study 2023. The Lancet, 406 (10518), 2461-2482. doi: 10.1016/S0140-6736(25)01853-7

Global, regional, and national burden of chronic kidney disease in adults, 1990-2023, and its attributable risk factors: a systematic analysis for the Global Burden of Disease Study 2023

2025

Journal Article

A deep ensemble learning framework for brain tumor classification using data balancing and fine-tuning

Talukder, Md. Alamin, Islam, Md. Manowarul, Uddin, Md. Ashraf, Layek, Md. Abu, Acharjee, Uzzal Kumar, Bhuiyan, Touhid and Moni, Mohammad Ali (2025). A deep ensemble learning framework for brain tumor classification using data balancing and fine-tuning. Scientific Reports, 15 (1) 35251. doi: 10.1038/s41598-025-03752-8

A deep ensemble learning framework for brain tumor classification using data balancing and fine-tuning

2025

Journal Article

Machine learning models to identify significant factors of panic buying situation

Satu, Md. Shahriare, Riyad, Md. Mahmudul Hasan, Alahmadi, Tahani Jaser, Bhuiyan, Touhid and Moni, Mohammad Ali (2025). Machine learning models to identify significant factors of panic buying situation. Scientific Reports, 15 (1) 34705. doi: 10.1038/s41598-025-18222-4

Machine learning models to identify significant factors of panic buying situation

2025

Journal Article

Global age-sex-specific all-cause mortality and life expectancy estimates for 204 countries and territories and 660 subnational locations, 1950–2023: a demographic analysis for the Global Burden of Disease Study 2023

Schumacher, Austin E, Zheng, Peng, Barber, Ryan M, A, Bhoomadevi, Aalipour, Mohammad Amin, Aalruz, Hasan, Ababneh, Hazim S, Abaraogu, Ukachukwu O, Abbafati, Cristiana, Abbas, Nasir, Abbasifard, Mitra, Abbaspour, Faezeh, Abd Al Magied, Abdallah H A, Abd ElHafeez, Samar, Abdalla, Mohammed Altigani, Abdallah, Emad M, Abdel Razeq, Nadin M I, Abdel-Hameed, Reda, Abdel-Rahman, Wael M, Abd-Elsalam, Sherief, Abdelwahab, Omar Ahmed, Abdi, Parsa, Abdollahi, Arash, Abdoun, Meriem, Abdous, Arman, Abdulah, Deldar Morad, Abdulkader, Rizwan Suliankatchi, Abdullahi, Auwal, Abdulraheem, Abdullahi Salahudeen ... Murray, Christopher J L (2025). Global age-sex-specific all-cause mortality and life expectancy estimates for 204 countries and territories and 660 subnational locations, 1950–2023: a demographic analysis for the Global Burden of Disease Study 2023. The Lancet, 406 (10513), 1731-1810. doi: 10.1016/s0140-6736(25)01330-3

Global age-sex-specific all-cause mortality and life expectancy estimates for 204 countries and territories and 660 subnational locations, 1950–2023: a demographic analysis for the Global Burden of Disease Study 2023

2025

Journal Article

Multi-Teacher Knowledge Distillation and Ensemble Algorithm for Efficient Brain Tumor Classification in Resource-Constrained Environments with Explainable AI

Alim, Md. Samiul, Tamim, Mahir Shahriar, Sarkar, Shuvo, Yousuf, Mohammad Abu, Al-Moisheer, Asmaa Soliman, Alyam, Salem A. and Moni, Mohammad Ali (2025). Multi-Teacher Knowledge Distillation and Ensemble Algorithm for Efficient Brain Tumor Classification in Resource-Constrained Environments with Explainable AI. Knowledge-Based Systems, 330 114711, 114711-330. doi: 10.1016/j.knosys.2025.114711

Multi-Teacher Knowledge Distillation and Ensemble Algorithm for Efficient Brain Tumor Classification in Resource-Constrained Environments with Explainable AI

2025

Journal Article

Normalizing images in various weather and lighting conditions using ColorPix2Pix generative adversarial network

Tasnim, Sanjida, Mostafa, Ashif Mahmud, Morshed, Azmain, Shaiyaz, Namreen, Dipto, Shakib Mahmud, Aloteibi, Saad, Moni, Mohammad Ali, Alam, Md. Golam Rabiul and Alam, Md. Ashraful (2025). Normalizing images in various weather and lighting conditions using ColorPix2Pix generative adversarial network. Scientific Reports, 15 (1) 33904. doi: 10.1038/s41598-025-08675-y

Normalizing images in various weather and lighting conditions using ColorPix2Pix generative adversarial network

Availability

Dr Mohammad Ali Moni is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • 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.

  • Deep Leaning Model to identify Neuroimaging biomarkers

  • Deep Learning models to solve inverse problems utiling MRI/fMRI image

  • AI-based based model development for Magnetic Resonance Imaging

  • AI-based Model development for ECG/EEG study

Supervision history

Current supervision

  • 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

  • Doctor Philosophy

    Wearable devices and AI Models for Monitoring, Predicting and Assessment Post-stroke Recovery

    Principal Advisor

  • Doctor Philosophy

    Developing AI-based Discission Support System utilising multimodal data

    Principal Advisor

    Other advisors: Associate Professor Asaduzzaman Khan

  • Doctor Philosophy

    Robust and Explainable AI to Solve Clinical Problems

    Principal Advisor

    Other advisors: Associate Professor Asaduzzaman Khan

  • 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

Enquiries

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