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

417 works between 2012 and 2026
All (417) Book (2) Journal Article (356) Conference Publication (53) Book Chapter (6)

341 - 360 of 417 works

2021

Journal Article

Ensemble of Convolutional Neural Networks to diagnose Acute Lymphoblastic Leukemia from microscopic images

Mondal, Chayan, Hasan, Md. Kamrul, Ahmad, Mohiuddin, Awal, Md. Abdul, Jawad, Md. Tasnim, Dutta, Aishwariya, Islam, Md. Rabiul and Moni, Mohammad Ali (2021). Ensemble of Convolutional Neural Networks to diagnose Acute Lymphoblastic Leukemia from microscopic images. Informatics in Medicine Unlocked, 27 100794, 100794. doi: 10.1016/j.imu.2021.100794

Ensemble of Convolutional Neural Networks to diagnose Acute Lymphoblastic Leukemia from microscopic images

2021

Conference Publication

COVID-Hero: machine learning based COVID-19 awareness enhancement mobile game for children

Satu, Md. Shahriare, Mizan, K. Shayekh Ebne, Jerin, Syeda Anika, Whaiduzzaman, Md, Barros, Alistair, Ahmed, Kawsar and Moni, Mohammad Ali (2021). COVID-Hero: machine learning based COVID-19 awareness enhancement mobile game for children. First International Conference on Applied Intelligence and Informatics, AII 2021, Online, 30-31 July 2021. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-82269-9_25

COVID-Hero: machine learning based COVID-19 awareness enhancement mobile game for children

2021

Conference Publication

Machine learning and bioinformatics models to identify gene expression patterns of glioblastoma associated with disease progression and mortality

Choudhury, Zakia Zinat, Chowdhury, Utpala Nanda, Ahmad, Shamim, Islam, M. Babul, Quinn, Julian M.W. and Moni, Mohammad Ali (2021). Machine learning and bioinformatics models to identify gene expression patterns of glioblastoma associated with disease progression and mortality. International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, Rajshahi, Bangladesh, 26-27 December 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IC4ME253898.2021.9768525

Machine learning and bioinformatics models to identify gene expression patterns of glioblastoma associated with disease progression and mortality

2021

Journal Article

Clinically applicable machine learning approaches to identify attributes of Chronic Kidney Disease (CKD) for use in low-cost diagnostic screening

Rashed-Al-Mahfuz, Md., Haque, Abedul, Azad, Akm, Alyami, Salem A., Quinn, Julian M. W. and Moni, Mohammad Ali (2021). Clinically applicable machine learning approaches to identify attributes of Chronic Kidney Disease (CKD) for use in low-cost diagnostic screening. IEEE Journal of Translational Engineering in Health and Medicine, 9 4900511, 1-11. doi: 10.1109/jtehm.2021.3073629

Clinically applicable machine learning approaches to identify attributes of Chronic Kidney Disease (CKD) for use in low-cost diagnostic screening

2021

Journal Article

Attribute driven temporal active online community search

Das, Badhan Chandra, Anwar, Md. Musfique, Bhuiyan, Md. Al-Amin, Sarker, Iqbal H., Alyami, Salem A. and Moni, Mohammad Ali (2021). Attribute driven temporal active online community search. IEEE Access, 9, 93976-93989. doi: 10.1109/access.2021.3093368

Attribute driven temporal active online community search

2020

Conference Publication

Drug compound prediction-based analysis of cigarette smoking to Pancreatic Cancer patients: a bioinformatics study

Taz, Tasnimul Alam, Kawsar, Md, Siddique, Sinthia, Ahmed, Kawsar, Moni, Mohammad Ali and Paul, Bikash Kumar (2020). Drug compound prediction-based analysis of cigarette smoking to Pancreatic Cancer patients: a bioinformatics study. IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), Bhubaneswar, India, 26-27 December 2020. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WIECON-ECE52138.2020.9397979

Drug compound prediction-based analysis of cigarette smoking to Pancreatic Cancer patients: a bioinformatics study

2020

Conference Publication

Bioinformatics approach to analyze gene expression profile and comorbidities of gastric cancer

Datta, Ratri, Podder, Nitun Kumar, Rana, Humayan Kabir, Islam, Md Khaled Ben and Moni, Mohammad Ali (2020). Bioinformatics approach to analyze gene expression profile and comorbidities of gastric cancer. 2020 23rd International Conference on Computer and Information Technology (ICCIT), Dhaka, Bangladesh, 19-21 December 2020. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCIT51783.2020.9392587

Bioinformatics approach to analyze gene expression profile and comorbidities of gastric cancer

2020

Journal Article

Gene expression profiling of SARS-CoV-2 infections reveal distinct primary lung cell and systemic immune infection responses that identify pathways relevant in COVID-19 disease

Moni, Mohammad Ali, Quinn, Julian M. W., Sinmaz, Nese and Summers, Matthew A. (2020). Gene expression profiling of SARS-CoV-2 infections reveal distinct primary lung cell and systemic immune infection responses that identify pathways relevant in COVID-19 disease. Briefings in Bioinformatics, 22 (2), 1324-1337. doi: 10.1093/bib/bbaa376

Gene expression profiling of SARS-CoV-2 infections reveal distinct primary lung cell and systemic immune infection responses that identify pathways relevant in COVID-19 disease

2020

Conference Publication

Identifying the stability of couple relationship applying different machine learning techniques

Satu, Md. Shahriare, Howlader, K. C., Hosen, Md Parvej, Chowdhury, Noton and Moni, Mohammad Ali (2020). Identifying the stability of couple relationship applying different machine learning techniques. 2020 11th International Conference on Electrical and Computer Engineering (ICECE), Dhaka, Bangladesh, 17-19 December 2020. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICECE51571.2020.9393131

Identifying the stability of couple relationship applying different machine learning techniques

2020

Journal Article

A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients

Ahamad, Md. Martuza, Aktar, Sakifa, Rashed-Al-Mahfuz, Md., Uddin, Shahadat, Liò, Pietro, Xu, Haoming, Summers, Matthew A., Quinn, Julian M.W. and Moni, Mohammad Ali (2020). A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients. Expert Systems with Applications, 160 113661, 113661. doi: 10.1016/j.eswa.2020.113661

A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients

2020

Journal Article

Design of novel viral attachment inhibitors of the spike glycoprotein (S) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) through virtual screening and dynamics

Oany, Arafat Rahman, Mia, Mamun, Pervin, Tahmina, Junaid, Md., Hosen, S. M. Zahid and Moni, Mohammad Ali (2020). Design of novel viral attachment inhibitors of the spike glycoprotein (S) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) through virtual screening and dynamics. International Journal of Antimicrobial Agents, 56 (6) 106177, 106177. doi: 10.1016/j.ijantimicag.2020.106177

Design of novel viral attachment inhibitors of the spike glycoprotein (S) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) through virtual screening and dynamics

2020

Journal Article

A system biological approach to investigate the genetic profiling and comorbidities of type 2 diabetes

Podder, Nitun Kumar, Rana, Humayan Kabir, Azam, Md. Shafiul, Rana, Md. Shohel, Akhtar, Mst. Rashida, Rahman, Md Rezanur, Rahman, Md Habibur and Moni, Mohammad Ali (2020). A system biological approach to investigate the genetic profiling and comorbidities of type 2 diabetes. Gene Reports, 21 100830, 1-13. doi: 10.1016/j.genrep.2020.100830

A system biological approach to investigate the genetic profiling and comorbidities of type 2 diabetes

2020

Journal Article

Machine learning and bioinformatics models to identify pathways that mediate influences of welding fumes on cancer progression

Rana, Humayan Kabir, Akhtar, Mst. Rashida, Islam, M. Babul, Ahmed, Mohammad Boshir, Lió, Pietro, Huq, Fazlul, Quinn, Julian M. W. and Moni, Mohammad Ali (2020). Machine learning and bioinformatics models to identify pathways that mediate influences of welding fumes on cancer progression. Scientific Reports, 10 (1) 2795, 2795. doi: 10.1038/s41598-020-57916-9

Machine learning and bioinformatics models to identify pathways that mediate influences of welding fumes on cancer progression

2020

Journal Article

Zeolite synthesis from low-cost materials and environmental applications: a review

Khaleque, Abdul, Alam, Md Masruck, Hoque, Mozammel, Mondal, Shuvodip, Haider, Jahid Bin, Xu, Bentuo, Johir, M. A.H., Karmakar, Aneek Krishna, Zhou, J. L., Ahmed, Mohammad Boshir and Moni, Mohammad Ali (2020). Zeolite synthesis from low-cost materials and environmental applications: a review. Environmental Advances, 2 100019, 100019. doi: 10.1016/j.envadv.2020.100019

Zeolite synthesis from low-cost materials and environmental applications: a review

2020

Journal Article

Analysis of topological properties and drug discovery for bipolar disorder and associated diseases: a bioinformatics approach

Shadhin, Khairul Alam, Hasan, Md. Rakibul, Paul, Bikash Kumar, Ahmed, Kawsar, Moni, Mohammad Ali, Kahrizi, Danial, Bhuyian, Touhid and Ibrahim, Sobhy M. (2020). Analysis of topological properties and drug discovery for bipolar disorder and associated diseases: a bioinformatics approach. Cellular and Molecular Biology, 66 (7), 152-160. doi: 10.14715/cmb/2020.66.7.23

Analysis of topological properties and drug discovery for bipolar disorder and associated diseases: a bioinformatics approach

2020

Journal Article

Five insights from the Global Burden of Disease Study 2019

Abbafati, Cristiana, Abbas, Kaja M., Abbasi, Mohammad, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abbastabar, Hedayat, Abd-Allah, Foad, Abdelalim, Ahmed, Abdollahi, Mohammad, Abdollahpour, Ibrahim, Abedi, Aidin, Abedi, Parisa, Abegaz, Kedir Hussein, Abolhassani, Hassan, Abosetugn, Akine Eshete, Aboyans, Victor, Abrams, Elissa M., Abreu, Lucas Guimaraes, Abrigo, Michael R. M., Abu Haimed, Abdulaziz Khalid, Abualhasan, Ahmed, Abu-Gharbieh, Eman, Abu-Raddad, Laith Jamal, Abushouk, Abdelrahman I., Acebedo, Alyssa, Ackerman, Ilana N., Adabi, Maryam, Adair, Tim, Adamu, Abdu A. ... Murray, Christopher J. L. (2020). Five insights from the Global Burden of Disease Study 2019. Lancet, 396 (10258), 1135-1159.

Five insights from the Global Burden of Disease Study 2019

2020

Journal Article

Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach

Al-Mustanjid, Md., Mahmud, S.M. Hasan, Royel, Md. Rejaul Islam, Rahman, Md. Habibur, Islam, Tania, Rahman, Md. Rezanur and Moni, Mohammad Ali (2020). Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach. Genomics, 112 (5), 3416-3426. doi: 10.1016/j.ygeno.2020.06.001

Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach

2020

Journal Article

Pathogenetic profiling of COVID-19 and SARS-like viruses

Nain, Zulkar, Rana, Humayan Kabir, Liò, Pietro, Islam, Sheikh Mohammed Shariful, Summers, Matthew A and Moni, Mohammad Ali (2020). Pathogenetic profiling of COVID-19 and SARS-like viruses. Briefings in Bioinformatics, 22 (2), 1175-1196. doi: 10.1093/bib/bbaa173

Pathogenetic profiling of COVID-19 and SARS-like viruses

2020

Journal Article

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017

Reiner, Robert C., Wiens, Kirsten E., Deshpande, Aniruddha, Baumann, Mathew M., Lindstedt, Paulina A., Blacker, Brigette F., Troeger, Christopher E., Earl, Lucas, Munro, Sandra B., Abate, Degu, Abbastabar, Hedayat, Abd-Allah, Foad, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Getaneh, Abegaz, Kedir Hussein, Abreu, Lucas Guimaraes, Abrigo, Michael R. M., Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adabi, Maryam, Adebayo, Oladimeji M., Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O., Adham, Davoud, Adhena, Beyene Meressa, Afarideh, Mohsen ... Hay, Simon I. (2020). Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017. Lancet, 395 (10239), 1779-1801. doi: 10.1016/S0140-6736(20)30114-8

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017

2020

Journal Article

A systematic review of network studies based on administrative health data

Karim, Shakir, Uddin, Shahadat, Imam, Tasadduq and Moni, Mohammad Ali (2020). A systematic review of network studies based on administrative health data. International Journal of Environmental Research and Public Health, 17 (7) 2568, 2568. doi: 10.3390/ijerph17072568

A systematic review of network studies based on administrative health data

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

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