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Dr Mohammad Ali Moni
Dr

Mohammad Ali Moni

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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

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

Works

Search Professor Mohammad Ali Moni’s works on UQ eSpace

323 works between 2012 and 2024

61 - 80 of 323 works

2023

Journal Article

A robust and clinically applicable deep learning model for early detection of Alzheimer's

Rana, Md Masud, Islam, Md Manowarul, Talukder, Md. Alamin, Uddin, Md Ashraf, Aryal, Sunil, Alotaibi, Naif, Alyami, Salem A., Hasan, Khondokar Fida and Moni, Mohammad Ali (2023). A robust and clinically applicable deep learning model for early detection of Alzheimer's. IET Image Processing, 17 (14), 3959-3975. doi: 10.1049/ipr2.12910

A robust and clinically applicable deep learning model for early detection of Alzheimer's

2023

Journal Article

StackFBAs: detection of fetal brain abnormalities using CNN with stacking strategy from MRI images

Chowdhury, Anjir Ahmed, Hasan Mahmud, S.M., Shahjalal Hoque, Khadija Kubra, Ahmed, Kawsar, Bui, Francis M., Lio, Pietro, Moni, Mohammad Ali and Al-Zahrani, Fahad Ahmed (2023). StackFBAs: detection of fetal brain abnormalities using CNN with stacking strategy from MRI images. Journal of King Saud University - Computer and Information Sciences, 35 (8) 101647, 101647. doi: 10.1016/j.jksuci.2023.101647

StackFBAs: detection of fetal brain abnormalities using CNN with stacking strategy from MRI images

2023

Journal Article

SafetyMed: A novel IoMT intrusion detection system using CNN-LSTM hybridization

Faruqui, Nuruzzaman, Yousuf, Mohammad Abu, Whaiduzzaman, Md, Azad, AKM, Alyami, Salem A., Liò, Pietro, Kabir, Muhammad Ashad and Moni, Mohammad Ali (2023). SafetyMed: A novel IoMT intrusion detection system using CNN-LSTM hybridization. Electronics, 12 (17) 3541, 3541. doi: 10.3390/electronics12173541

SafetyMed: A novel IoMT intrusion detection system using CNN-LSTM hybridization

2023

Journal Article

Systems biology approach discovers comorbidity interaction of Parkinson's disease with psychiatric disorders utilizing brain transcriptome

Nashiry, Md Asif, Sumi, Shauli Sarmin, Alyami, Salem A. and Moni, Mohammad Ali (2023). Systems biology approach discovers comorbidity interaction of Parkinson's disease with psychiatric disorders utilizing brain transcriptome. Frontiers in Molecular Neuroscience, 16 1232805, 1232805. doi: 10.3389/fnmol.2023.1232805

Systems biology approach discovers comorbidity interaction of Parkinson's disease with psychiatric disorders utilizing brain transcriptome

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, Abdul Aziz, Jeza Muhamad, 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. The Lancet Neurology, 22 (8), 685-711. doi: 10.1016/S1474-4422(23)00195-3

Global, regional, and national burden of meningitis and its aetiologies, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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.

What baseline and intervention characteristics predict walking speed six months after stroke?

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.

Global, regional, and national burden of meningitis and its aetiologies, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

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

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

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. doi: 10.3390/info14070376

A comparison of machine learning techniques for the detection of type-2 diabetes mellitus: experiences from Bangladesh

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

An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis

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

Ensemble learning for disease prediction: a review

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. doi: 10.3390/diagnostics13122106

A novel hybrid approach for classifying osteosarcoma using deep feature extraction and multilayer perceptron

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

Machine learning-based biomedical antenna for brain tumor detection

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

A dynamic topic identification and labeling approach for COVID-19 tweets

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.

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

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

The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells

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

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

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

Machine learning-based model to predict heart disease in early stage employing different feature selection techniques

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

HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

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

Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019

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

  • 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

    Understanding the pathophysiology of stroke using bioinformatics and statistical genetics approaches

    Principal Advisor

    Other advisors: Associate Professor Asaduzzaman Khan, Dr Jian Zeng

  • Doctor Philosophy

    Robust and Explainable AI to Solve Clinical Problems

    Principal Advisor

    Other advisors: Associate Professor Asaduzzaman Khan

  • Master Philosophy

    Advancing Maternal-Fetal Health in Underserved Communities: A Computer Vision Approach

    Principal Advisor

  • Doctor Philosophy

    Service extension and cost minimization in healthcare management of peripheral healthcare organizations in Bangladesh: analysis for service improvement

    Associate Advisor

    Other advisors: Associate Professor Asaduzzaman Khan

Media

Enquiries

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communications@uq.edu.au