Skip to menu Skip to content Skip to footer
Associate Professor Sally Shrapnel
Associate Professor

Sally Shrapnel

Email: 
Phone: 
+61 7 336 56931

Overview

Background

Dr Sally Shrapnel is an internationally recognised interdisciplinary scientist whose research spans quantum physics, artificial intelligence, digital medicine, and philosophy. With a unique career trajectory bridging clinical medicine and cutting-edge quantum technologies, Dr Shrapnel is committed to solving foundational and applied problems that cross traditional disciplinary boundaries.

A registered medical practitioner and Fellow of the Royal Australian College of General Practitioners, she brings over two decades of clinical experience in Tasmania, Queensland, and the UK. After earning an MSc in Bioengineering from Imperial College London, she pursued a PhD in Quantum Artificial Intelligence—focusing on quantum causal inference—which launched her second career as a quantum physicist.

Currently, Dr Shrapnel is Associate Professor of Physics at The University of Queensland and Deputy Director of the ARC Centre of Excellence for Engineered Quantum Systems (EQUS). Her research addresses two fundamental questions:

  • What does quantum theory reveal about the nature of reality?
  • Can quantum resources be harnessed to design faster, more efficient AI algorithms?

These inquiries drive her leading contributions in Quantum Foundations and Quantum Machine Learning, where she develops novel theoretical frameworks and algorithms that aim to unlock the quantum advantage in emerging technologies. As Program Lead for Quantum Technologies for Health at the Queensland Digital Health Centre, Dr Shrapnel is also preparing the state’s healthcare ecosystem for the next technological revolution—bringing quantum tools into real-world applications in health and medicine.

A passionate advocate for interdisciplinary research, Dr Shrapnel continues to publish widely across quantum physics, computer science, digital health, and the philosophy of science. Her work exemplifies the power of rigorous, cross-disciplinary thinking to address some of the most profound and practical challenges of our time.

Availability

Associate Professor Sally Shrapnel is:
Available for supervision

Qualifications

  • Bachelor of Medical Science, The University of Queensland
  • Bachelor of Medicine and Surgery and Medical Science, The University of Queensland
  • Masters (Coursework) of Science, Imperial College
  • Doctor of Philosophy, The University of Queensland

Works

Search Professor Sally Shrapnel’s works on UQ eSpace

60 works between 2014 and 2025

1 - 20 of 60 works

2025

Other Outputs

Global geographic and socioeconomic disparities in COVID-Associated AKI: a systematic review and meta-analysis

Dai, Danyang, Gois, Pedro Franca, Simpson, Digby, Hedfi, Souhayel, Shrapnel, Sally and Pole, Jason D. (2025). Global geographic and socioeconomic disparities in COVID-Associated AKI: a systematic review and meta-analysis. Centre for Health Services Research; Centre for Online Health.

Global geographic and socioeconomic disparities in COVID-Associated AKI: a systematic review and meta-analysis

2025

Journal Article

A de Finetti theorem for quantum causal structures

Costa, Fabio, Barrett, Jonathan and Shrapnel, Sally (2025). A de Finetti theorem for quantum causal structures. Quantum, 9 1628, 1628. doi: 10.22331/q-2025-02-11-1628

A de Finetti theorem for quantum causal structures

2025

Conference Publication

Prevalence of Acute Kidney Injury throughout COVID-19: A Systematic review and meta-analysis

Franca Gois, Pedro Henrique, Gois, Pedro Franca, Simpson, Digby, Hedfi, Souhayel, Shrapnel, Sally and Pole, Jason D. (2025). Prevalence of Acute Kidney Injury throughout COVID-19: A Systematic review and meta-analysis. ISN World Congress of Nephrology (WCN) 2025, New Delhi, India, 6 - 9 February 2025. New York, NY United States: Elsevier. doi: 10.1016/j.ekir.2024.11.1083

Prevalence of Acute Kidney Injury throughout COVID-19: A Systematic review and meta-analysis

2025

Conference Publication

Global Geographic and Socio-Economic Disparities in COVID-Associated Acute Kidney Injury: A Systematic Review and Meta-analysis

Franca Gois, Pedro Henrique, Gois, Pedro Franca, Simpson, Digby, Hedfi, Souhayel, Shrapnel, Sally and Pole, Jason D. (2025). Global Geographic and Socio-Economic Disparities in COVID-Associated Acute Kidney Injury: A Systematic Review and Meta-analysis. ISN World Congress of Nephrology (WCN) 2025, New Delhi, India, 6 - 9 February 2025. New York, NY United States: Elsevier. doi: 10.1016/j.ekir.2024.11.1085

Global Geographic and Socio-Economic Disparities in COVID-Associated Acute Kidney Injury: A Systematic Review and Meta-analysis

2024

Journal Article

Quantum kernel machine learning with continuous variables

Henderson, Laura J., Goel, Rishi and Shrapnel, Sally (2024). Quantum kernel machine learning with continuous variables. Quantum, 8 1570. doi: 10.22331/q-2024-12-17-1570

Quantum kernel machine learning with continuous variables

2024

Journal Article

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

Mesinovic, Munib, Wong, Xin Ci, Rajahram, Giri Shan, Citarella, Barbara Wanjiru, Peariasamy, Kalaiarasu M., van Someren Greve, Frank, Olliaro, Piero, Merson, Laura, Clifton, Lei, Kartsonaki, Christiana, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Acker, Andrew, Adachi, Shingo, Adam, Elisabeth, Adriano, Enrico, Adrião, Diana, Ageel, Saleh Al, Ahmed, Shakeel, Aiello, Marina, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait ... Zucman, David (2024). At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods. Scientific Reports, 14 (1) 16387. doi: 10.1038/s41598-024-63212-7

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

2024

Conference Publication

AKI in Intensive Care Unit (ICU) Patients in the Omicron Surge: Insights from a Multinational Study

Gois, Pedro Henrique Franca, Dai, Danyang, Shrapnel, Sally, Wainstein, Marina, Ghadimi, Moji, Spyrison, Nicholas S., Claure-Del Granado, Rolando and Pole, Jason D. (2024). AKI in Intensive Care Unit (ICU) Patients in the Omicron Surge: Insights from a Multinational Study. Kidney Week, San Diego, CA United States, 24-27 October 2024. Philadelphia, PA United States: Wolters Kluwer. doi: 10.1681/asn.2024j8evcrgq

AKI in Intensive Care Unit (ICU) Patients in the Omicron Surge: Insights from a Multinational Study

2024

Journal Article

Lightweight transformers for clinical natural language processing

Rohanian, Omid, Nouriborji, Mohammadmahdi, Jauncey, Hannah, Kouchaki, Samaneh, Nooralahzadeh, Farhad, Clifton, Lei, Merson, Laura, Clifton, David A., Abbas, Ali, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Jabal, Kamal Abu, Salah, Nashat Abu, Acharya, Subhash, Acker, Andrew, Adachi, Shingo, Adam, Elisabeth, Adewhajah, Francisca, Adriano, Enrico, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Aiello, Marina, Ainscough, Kate, Airlangga, Eka ... Zucman, David (2024). Lightweight transformers for clinical natural language processing. Natural Language Engineering, 30 (5), 887-914. doi: 10.1017/S1351324923000542

Lightweight transformers for clinical natural language processing

2024

Journal Article

Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation

Merson, Laura, Duque, Sara, Garcia-Gallo, Esteban, Yeabah, Trokon Omarley, Rylance, Jamie, Diaz, Janet, Flahault, Antoine, Abdalasalam, Sabriya, Abdalhadi, Alaa Abdalfattah, Abdalla, Walaa, Abdalla, Naana Reyam, Abdalrheem, Almthani Hamza, Abdalsalam, Ashraf, Abdeewi, Saedah, Abdelgaum, Esraa Hassan, Abdelhalim, Mohamed, Abdelkabir, Mohammed, Abdukahil, Sheryl Ann, Abdulbaqi, Lamees Adil, Abdulhamid, Widyan, Abdulhamid, Salaheddin, Abdulkadir, Nurul Najmee, Abdulwahed, Eman, Abdunabi, Rawad, Abe, Ryuzo, Abel, Laurent, Abodina, Ahmed Mohammed, Abouelmagd, Khaled, Abrous, Amal ... Zucman, David (2024). Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation. Epidemiologia, 5 (3), 557-580. doi: 10.3390/epidemiologia5030039

Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation

2024

Journal Article

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers

Kamel Rahimi, Amir, Pienaar, Oliver, Ghadimi, Moji, Canfell, Oliver J., Pole, Jason D., Shrapnel, Sally, van der Vegt, Anton H. and Sullivan, Clair (2024). Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers. Journal of Medical Internet Research, 26 e49655, 1-29. doi: 10.2196/49655

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers

2024

Journal Article

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Citarella, Barbara Wanjiru, Kartsonaki, Christiana, Ibáñez-Prada, Elsa D., Gonçalves, Bronner P., Baruch, Joaquin, Escher, Martina, Pritchard, Mark G., Wei, Jia, Philippy, Fred, Dagens, Andrew, Hall, Matthew, Lee, James, Kutsogiannis, Demetrios James, Wils, Evert-Jan, Fernandes, Marília Andreia, Tirupakuzhi Vijayaraghavan, Bharath Kumar, Panda, Prasan Kumar, Martin-Loeches, Ignacio, Ohshimo, Shinichiro, Fatoni, Arie Zainul, Horby, Peter, Dunning, Jake, Rello, Jordi, Merson, Laura, Rojek, Amanda, Vaillant, Michel, Olliaro, Piero, Reyes, Luis Felipe, Moharam, S.A. ... Zucman, David (2024). Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms. Heliyon, 10 (10) e29591, e29591. doi: 10.1016/j.heliyon.2024.e29591

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

2024

Conference Publication

Validation Of The Extended Kdigo Definition To Diagnose Acute Kidney Injury In A General Hospital Population Using The Mimic-IV Dataset

Wainstein, Marina, Edward, Eleanor, Spyrison, Nicholas, Rahimi, Amir Kamel, Ghadimi, Moji, Johnson, David and Shrapnel, Sally (2024). Validation Of The Extended Kdigo Definition To Diagnose Acute Kidney Injury In A General Hospital Population Using The Mimic-IV Dataset. ISN World Congress of Nephrology (WCN) 2024, Buenos Aires, Argentina, 13-16 April 2024. New York, NY United States: Elsevier. doi: 10.1016/j.ekir.2024.02.537

Validation Of The Extended Kdigo Definition To Diagnose Acute Kidney Injury In A General Hospital Population Using The Mimic-IV Dataset

2024

Journal Article

Quantum kernel evaluation via Hong-Ou-Mandel interference

Bowie, Cassandra, Shrapnel, Sally and Kewming, Michael (2024). Quantum kernel evaluation via Hong-Ou-Mandel interference. Quantum Science and Technology, 9 (1) 015001, 1-10. doi: 10.1088/2058-9565/acfba9

Quantum kernel evaluation via Hong-Ou-Mandel interference

2024

Book Chapter

Artificial intelligence for diabetes in the hospital

Sly, Benjamin P., Shrapnel, Sally and Sullivan, Clair M. (2024). Artificial intelligence for diabetes in the hospital. Diabetes digital health, telehealth, and artificial intelligence. (pp. 353-366) edited by David C. Klonoff, David Kerr and Juan C. Espinoza. London, United Kingdom: Elsevier. doi: 10.1016/b978-0-443-13244-5.00021-3

Artificial intelligence for diabetes in the hospital

2023

Conference Publication

A Systematic Review of Externally Validated Machine Learning Models for Predicting AKI in General Hospital Patients

Wainstein, Marina, Flanagan, Emily K., Johnson, David W. and Shrapnel, Sally (2023). A Systematic Review of Externally Validated Machine Learning Models for Predicting AKI in General Hospital Patients. Kidney Week, Philadelphia, PA United States, 1-5 November 2023. Philadelphia, PA United States: Lippincott Williams & Wilkins. doi: 10.1681/asn.20233411s11066a

A Systematic Review of Externally Validated Machine Learning Models for Predicting AKI in General Hospital Patients

2023

Journal Article

Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy

Kamel Rahimi, Amir, Ghadimi, Moji, van der Vegt, Anton H., Canfell, Oliver J., Pole, Jason D., Sullivan, Clair and Shrapnel, Sally (2023). Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy. BMC Medical Informatics and Decision Making, 23 (1) 207, 1-14. doi: 10.1186/s12911-023-02306-0

Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy

2023

Journal Article

Major adverse cardiovascular events (MACE) in patients with severe COVID-19 registered in the ISARIC WHO clinical characterization protocol: a prospective, multinational, observational study

Reyes, Luis Felipe, Garcia-Gallo, Esteban, Murthy, Srinivas, Fuentes, Yuli V., Serrano, Cristian C., Ibáñez-Prada, Elsa D., Lee, James, Rojek, Amanda, Citarella, Barbara Wanjiru, Gonçalves, Bronner P., Dunning, Jake, Rätsep, Indrek, Viñan-Garces, Andre Emilio, Kartsonaki, Christiana, Rello, Jordi, Martin-Loeches, Ignacio, Shankar-Hari, Manu, Olliaro, Piero L., Merson, Laura, Abbas, Ali, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abebrese, Franklina Korkor, Abel, Laurent, Abrous, Amal, Absil, Lara, Acharya, Subhash, Acker, Andrew ... Zucman, David (2023). Major adverse cardiovascular events (MACE) in patients with severe COVID-19 registered in the ISARIC WHO clinical characterization protocol: a prospective, multinational, observational study. Journal of Critical Care, 77 154318, 1-13. doi: 10.1016/j.jcrc.2023.154318

Major adverse cardiovascular events (MACE) in patients with severe COVID-19 registered in the ISARIC WHO clinical characterization protocol: a prospective, multinational, observational study

2023

Journal Article

A multi-country analysis of COVID-19 hospitalizations by vaccination status

Gonçalves, Bronner P., Jassat, Waasila, Baruch, Joaquín, Hashmi, Madiha, Rojek, Amanda, Dasgupta, Abhishek, Martin-Loeches, Ignacio, Reyes, Luis Felipe, Piubelli, Chiara, Citarella, Barbara Wanjiru, Kartsonaki, Christiana, Lefèvre, Benjamin, López Revilla, José W., Lunn, Miles, Harrison, Ewen M., Kraemer, Moritz U. G., Shrapnel, Sally, Horby, Peter, Bisoffi, Zeno, Olliaro, Piero L, Merson, Laura, ISARIC Clinical Characterisation Group and Ghadimi, Moji (2023). A multi-country analysis of COVID-19 hospitalizations by vaccination status. Med, 4 (11), 797-812.e2. doi: 10.1016/j.medj.2023.08.005

A multi-country analysis of COVID-19 hospitalizations by vaccination status

2023

Journal Article

Validation of extracorporeal membrane oxygenation mortality prediction and severity of illness scores in an international COVID-19 cohort

Shah, Neel, Xue, Bing, Xu, Ziqi, Yang, Hanqing, Marwali, Eva, Dalton, Heidi, Payne, Philip P. R., Lu, Chenyang, Said, Ahmed S., Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Absil, Lara, Acker, Andrew, Adrião, Diana, Hssain, Ali Ait, Akwani, Chika, Al Qasim, Eman, Alalqam, Razi, Al-dabbous, Tala, Alex, Beatrice, Al-Fares, Abdulrahman, Alfoudri, Huda, Aliudin, Jeffrey, Alves, João, Alves, Rita, Alves, João Melo, Cabrita, Joana Alves, Amaral, Maria, Amira, Nur ... ISARIC Clinical Characterisation Group (2023). Validation of extracorporeal membrane oxygenation mortality prediction and severity of illness scores in an international COVID-19 cohort. Artificial Organs, 47 (9), 1490-1502. doi: 10.1111/aor.14542

Validation of extracorporeal membrane oxygenation mortality prediction and severity of illness scores in an international COVID-19 cohort

2023

Journal Article

Liver injury in hospitalized patients with COVID-19: An International observational cohort study

Vijayaraghavan, Bharath Kumar Tirupakuzhi, Bishnu, Saptarshi, Baruch, Joaquin, Citarella, Barbara Wanjiru, Kartsonaki, Christiana, Meeyai, Aronrag, Mohamed, Zubair, Ohshimo, Shinichiro, Lefèvre, Benjamin, Al-Fares, Abdulrahman, Calvache, Jose A., Taccone, Fabio Silvio, Olliaro, Piero, Merson, Laura, Adhikari, Neill K.J., Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Acker, Andrew, Adam, Elisabeth, Adrião, Diana, Al Ageel, Saleh, Ainscough, Kate, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako ... the ISARIC Clinical Characterisation Group (2023). Liver injury in hospitalized patients with COVID-19: An International observational cohort study. PLoS One, 18 (9 September) e0277859, 1-17. doi: 10.1371/journal.pone.0277859

Liver injury in hospitalized patients with COVID-19: An International observational cohort study

Funding

Current funding

  • 2025 - 2027
    Operationally robust quantum machine learning for digital health
    Quantum and Advanced Technologies Co-Investment Program
    Open grant
  • 2025 - 2028
    The View From Somewhere: embodied agents and the quantum perspective
    ARC Discovery Projects
    Open grant

Past funding

  • 2022 - 2023
    SMART Project - Towards Systematic Maturation of Analytics and System Redesign to Transform (SMART) Healthcare and Public Health Research
    Queensland Health
    Open grant
  • 2021 - 2023
    Machine learning prediction of Acute Kidney Injury in hospitalised patients with COVID-19
    Digital Health CRC
    Open grant
  • 2021 - 2022
    Causal Bayesian Networks for COVID
    Monash University
    Open grant
  • 2020 - 2025
    Enhanced data extraction and modelling from electronic medical records and phenotyping for clinical care, and research: Case studies in management of medication stewardship
    Digital Health CRC
    Open grant
  • 2020 - 2024
    Information as fuel for a quantum clock (Foundational Questions Institute grant administered by TUQIA)
    Foundational Questions Institute
    Open grant
  • 2019 - 2021
    'Are Quantum agents possible?' by Silicon Valley Community Foundation
    The University of Queensland in America, Inc
    Open grant
  • 2018 - 2025
    ARC Centre of Excellence for Engineered Quantum Systems (EQuS2)
    ARC Centres of Excellence
    Open grant

Supervision

Availability

Associate Professor Sally Shrapnel is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

    Characterising the impact of noise in quantum machine learning.

    Principal Advisor

    Other advisors: Dr Riddhi Gupta

  • Doctor Philosophy

    Perspectives on the de Broglie-Bohm interpretation

    Associate Advisor

    Other advisors: Professor Timothy Ralph, Dr Peter Evans

  • Doctor Philosophy

    Digital Health Methods for Evaluating Chronic Organ Injuries Resulting from Infectious Epidemics: Acute Kidney Injury post COVID-19 Omicron Surge as an Exemplar

    Associate Advisor

    Other advisors: Professor Jason Pole

  • Doctor Philosophy

    Predicting adverse diabetes events in hospitals using machine learning

    Associate Advisor

    Other advisors: Professor Clair Sullivan, Professor Jason Pole

Completed supervision

Media

Enquiries

For media enquiries about Associate Professor Sally Shrapnel's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au