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

338 works between 2012 and 2024
All (338) Journal Article (293) Book Chapter (4) Conference Publication (40) Book (1)

1 - 20 of 338 works

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 ... Dirac, M. Ashworth (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, 102924. doi: 10.1016/j.eclinm.2024.102924

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

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 ... Kyu, Hmwe (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

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

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

Prediction of white blood cell count during exercise: a comparison between standalone and hybrid intelligent algorithms

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

DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model

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. doi: 10.1038/s41598-024-66721-7

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)

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. doi: 10.1002/aisy.202400566

A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes

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, 100718. doi: 10.1016/j.simpa.2024.100718

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

2024

Conference Publication

EAH-Net: A Novel Ensemble Attention-Based Hybrid Architecture for Breast Cancer Diagnosis Utilizing Ultrasound Images

Hasan, Md. Zahid, Hossain, Shahed, Jim, Risul Islam, Bulbul, Abdullah Al-Mamun, Rahman, Md. Tanvir and Moni, Mohammad Ali (2024). EAH-Net: A Novel Ensemble Attention-Based Hybrid Architecture for Breast Cancer Diagnosis Utilizing Ultrasound Images. 1st International Workshop on Multimedia Computing for Health and Medicine (MCHM), Melbourne Australia, Oct 28-Nov 01, 2024. New York, NY, USA: ACM. doi: 10.1145/3688868.3689198

EAH-Net: A Novel Ensemble Attention-Based Hybrid Architecture for Breast Cancer Diagnosis Utilizing Ultrasound Images

2024

Journal Article

A robust deep learning approach for identification of RNA 5-methyluridine sites

Shaon, Md. Shazzad Hossain, Karim, Tasmin, Ali, Md. Mamun, Ahmed, Kawsar, Bui, Francis M., Chen, Li and Moni, Mohammad Ali (2024). A robust deep learning approach for identification of RNA 5-methyluridine sites. Scientific Reports, 14 (1) 25688. doi: 10.1038/s41598-024-76148-9

A robust deep learning approach for identification of RNA 5-methyluridine sites

2024

Journal Article

Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches

Hossain, Md Ali, Rahman, Mohammad Zahidur, Bhuiyan, Touhid and Moni, Mohammad Ali (2024). Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches. International Journal of Environmental Research and Public Health, 21 (11) 1392, 1392. doi: 10.3390/ijerph21111392

Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches

2024

Conference Publication

NewBreeze: A Comprehensive Solution to a Beginner-Friendly Arch Linux Distribution with Zen Kernel

Al Mamun, Abdullah, Najrul Howlader, S. M., Khanom, Shoma, Yousuf, Mohammad Abu and Moni, Mohammad Ali (2024). NewBreeze: A Comprehensive Solution to a Beginner-Friendly Arch Linux Distribution with Zen Kernel. International Conference on Trends in Electronics and Health Informatics TEHI 2023, Dhaka, Bangladesh, 26–27 December 2023. Singapore: Springer. doi: 10.1007/978-981-97-3937-0_14

NewBreeze: A Comprehensive Solution to a Beginner-Friendly Arch Linux Distribution with Zen Kernel

2024

Conference Publication

Sentiment Analysis in Twitter Data Using Machine Learning-Based Approach

Al Arafat, Kazi Abdullah, Roni, Mahmudur Rahman, Siddique, Sumaya, Yousuf, Mohammad Abu and Moni, Mohammad Ali (2024). Sentiment Analysis in Twitter Data Using Machine Learning-Based Approach. International Conference on Trends in Electronics and Health Informatics TEHI 2023, Dhaka, Bangladesh, 26–27 December 2023. Singapore: Springer. doi: 10.1007/978-981-97-3937-0_12

Sentiment Analysis in Twitter Data Using Machine Learning-Based Approach

2024

Conference Publication

Enhancing Image Forensics with Transformer: A Multi-head Attention Approach for Robust Metadata Analysis

Appel Mahmud Pranto, Md., Asad, Nafiz Al, Yousuf, Mohammad Abu, Uddin, Mohammed Nasir and Moni, Mohammad Ali (2024). Enhancing Image Forensics with Transformer: A Multi-head Attention Approach for Robust Metadata Analysis. International Conference on Trends in Electronics and Health Informatics TEHI 2023, Dhaka, Bangladesh, 26–27 December 2023. Singapore: Springer. doi: 10.1007/978-981-97-3937-0_45

Enhancing Image Forensics with Transformer: A Multi-head Attention Approach for Robust Metadata Analysis

2024

Journal Article

PollenNet: A novel architecture for high precision pollen grain classification through deep learning and explainable AI

Shamrat, F M Javed Mehedi, Idna Idris, Mohd Yamani, Zhou, Xujuan, Khalid, Majdi, Sharmin, Sharmin, Sharmin, Zeseya, Ahmed, Kawsar and Moni, Mohammad Ali (2024). PollenNet: A novel architecture for high precision pollen grain classification through deep learning and explainable AI. Heliyon, 10 (19) e38596, e38596. doi: 10.1016/j.heliyon.2024.e38596

PollenNet: A novel architecture for high precision pollen grain classification through deep learning and explainable AI

2024

Journal Article

Multi-View Soft Attention-Based Model for the Classification of Lung Cancer-Associated Disabilities

Esha, Jannatul Ferdous, Islam, Tahmidul, Pranto, Md. Appel Mahmud, Borno, Abrar Siam, Faruqui, Nuruzzaman, Yousuf, Mohammad Abu, Azad, AKM, Al-Moisheer, Asmaa Soliman, Alotaibi, Naif, Alyami, Salem A. and Moni, Mohammad Ali (2024). Multi-View Soft Attention-Based Model for the Classification of Lung Cancer-Associated Disabilities. Diagnostics, 14 (20) 2282, 2282. doi: 10.3390/diagnostics14202282

Multi-View Soft Attention-Based Model for the Classification of Lung Cancer-Associated Disabilities

2024

Journal Article

An improved K-means clustering algorithm towards an efficient data-driven modeling

Zubair, Md., Iqbal, Md. Asif, Shil, Avijeet, Chowdhury, M. J.M., Moni, Mohammad Ali and Sarker, Iqbal H. (2024). An improved K-means clustering algorithm towards an efficient data-driven modeling. Annals of Data Science, 11 (5), 1525-1544. doi: 10.1007/s40745-022-00428-2

An improved K-means clustering algorithm towards an efficient data-driven modeling

2024

Journal Article

Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques

Sutradhar, Ananda, Akter, Sharmin, Shamrat, F M Javed Mehedi, Ghosh, Pronab, Zhou, Xujuan, Idris, Mohd Yamani Idna Bin, Ahmed, Kawsar and Moni, Mohammad Ali (2024). Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques. Heliyon, 10 (17) e36556, e36556. doi: 10.1016/j.heliyon.2024.e36556

Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques

2024

Journal Article

Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021

Sirota, Sarah Brooke, Doxey, Matthew C, Dominguez, Regina-Mae Villanueva, Bender, Rose Grace, Vongpradith, Avina, Albertson, Samuel B, Novotney, Amanda, Burkart, Katrin, Carter, Austin, Abdi, Parsa, Abdoun, Meriem, Abebe, Ayele Mamo, Abegaz, Kedir Hussein, Aboagye, Richard Gyan, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abualruz, Hasan, Abu-Gharbieh, Eman, Aburuz, Salahdein, Adane, Mesafint Molla, Addo, Isaac Yeboah, Adekanmbi, Victor, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afzal, Muhammad Sohail, Afzal, Saira, Ahinkorah, Bright Opoku, Ahmad, Sajjad, Ahmed, Ayman ... Kyu, Hmwe Hmwe (2024). Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021. The Lancet Infectious Diseases. doi: 10.1016/s1473-3099(24)00430-4

Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021

2024

Journal Article

MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool

Sultan, Md. Fahim, Shaon, Md. Shazzad Hossain, Karim, Tasmin, Ali, Md. Mamun, Hasan, Md. Zahid, Ahmed, Kawsar, Bui, Francis M., Chen, Li, Dhasarathan, Vigneswaran and Moni, Mohammad Ali (2024). MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool. Heliyon, 10 (18) e37820, e37820. doi: 10.1016/j.heliyon.2024.e37820

MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool

2024

Journal Article

Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021

Han, Hannah, Letourneau, Ian D, Abate, Yohannes Habtegiorgis, Abdelmasseh, Michael, Abu-Gharbieh, Eman, Adane, Tigist Demssew, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmadi, Ali, Ahmed, Ayman, Alhalaiqa, Fadwa Naji, Al-Sabah, Salman Khalifah, Al-Worafi, Yaser Mohammed, Amu, Hubert, Andrei, Catalina Liliana, Anoushiravani, Amir, Arabloo, Jalal, Aravkin, Aleksandr Y, Ashraf, Tahira, Azadnajafabad, Sina, Baghcheghi, Nayereh, Bagherieh, Sara, Bantie, Berihun Bantie, Bardhan, Mainak, Basile, Guido, Bayleyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Bekele, Alehegn, Bhojaraja, Vijayalakshmi S ... Dirac, M Ashworth (2024). Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021. The Lancet Gastroenterology and Hepatology, 9 (9), 825-858. doi: 10.1016/S2468-1253(24)00157-2

Trends and levels of the global, regional, and national burden of appendicitis between 1990 and 2021: findings from the Global Burden of Disease Study 2021

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

    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

    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

    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

Enquiries

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