Overview
Background
Dr. Lord leads the Spectroscopy Lab at the School of the Environment, the University of Queensland. Her interdisciplinary research focuses on developing novel, rapid next-generation surveillance and diagnostic tools using infrared light and artificial intelligence. These tools are designed for detecting pathogens in humans and the environment and for characterizing disease-carrying vectors such as mosquitoes.
During the Zika epidemic, Dr. Lord pioneered the application of infrared spectroscopy for rapid Zika virus detection in mosquitoes, achieving results in less than 10 seconds. In 2022, in collaboration with the Australian Defence Force and Instituto Oswaldo Cruz in Brazil, she led a team that demonstrated for the first time that infrared light and AI could detect malaria through the skin—eliminating the need for blood samples.
As a Chief Investigator, Dr. Lord has secured research funding from several funding bodies including the Bill & Melinda Gates Foundation, USAID, NHMRC, AQIRF, and Grand Challenges Canada to develop rapid tools for large-scale disease surveillance. With her recent funding from the National Health and Medical Research Council, she is developing a smart trap for Ross River virus surveillance in partnership with Queensland Health.
Dr. Lord has published over 60 research works, and presented her findings at over 30 international conferences. Her groundbreaking research has been featured in hundreds of media outlets worldwide. Her contributions to global health have earned her numerous academic accolades, including being named a Fellow of the American Society of Tropical Medicine and Hygiene in 2024.
Beyond research, Dr. Lord leads the STEM Spotlight program, a STEM mentorship initiative that provides a safe and engaging space for students from culturally and linguistically diverse (CALD) communities. The program encourages students from underrepresented backgrounds to pursue careers in STEM while providing them the opportunity to be part of the STEM community in a safe space. In recognition of this work, she was awarded the Diversity and Inclusion Champion Award (2023) by the Department of Multicultural Affairs. Dr Lord has served/serves on numerous committees including the Australian of the year selection Committee (2023), the American Society of Tropical Medicine and Hygiene Scientific Committee, Young investigator award committee (ASTMH), Equity, Diversity and Inclusion committee (UQ).Between 2021-2024 she served as the vice president of African Professionals of Australia (QLD).
Current Research interests:
Vectors that transmit diseases including but not limited to mosquitoes, Triatomine species, ticks
Large scale surveillance tools for Vector-borne disease
Availability
- Dr Maggy Lord is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Doctor of Philosophy, Griffith University
Research interests
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Vector borne diseases
Surveillance tools for vector-borne diseases
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Artificial intelligence
Development of AI tools for vector-borne diseases
Research impacts
Demonstrated the capacity of infrared and Artificial intelligence to
1. Characterise mosquito species into age, species and infection
2. Detect Zika, Dengue and Chikungunya in seconds non-invasively in mosquitoes
3. Detect Wolbachia in mosquitoes non-invasively
4. Detect Trypanosoma cruzi in Triatomine species and faecal samples
5. Detect malaria non-invasively through the skin of human subjects
6. Detect soil-transmitted helminths non-invasively in experimental mouse
Works
Search Professor Maggy Lord’s works on UQ eSpace
2025
Journal Article
Identification of visible and near-infrared signature peaks for arboviruses and Plasmodium falciparum
Goh, Brendon, Soares Magalhães, Ricardo J., Ciocchetta, Silvia, Liu, Wenjun and Sikulu-Lord, Maggy T. (2025). Identification of visible and near-infrared signature peaks for arboviruses and Plasmodium falciparum. PLoS ONE, 20 (4 April) e0321362, e0321362. doi: 10.1371/journal.pone.0321362
2024
Journal Article
Rapid assessment of the blood-feeding histories of wild-caught malaria mosquitoes using mid-infrared spectroscopy and machine learning
Mwanga, Emmanuel P., Mchola, Idrisa S., Makala, Faraja E., Mshani, Issa H., Siria, Doreen J., Mwinyi, Sophia H., Abbasi, Said, Seleman, Godian, Mgaya, Jacqueline N., Jiménez, Mario González, Wynne, Klaas, Sikulu-Lord, Maggy T., Selvaraj, Prashanth, Okumu, Fredros O., Baldini, Francesco and Babayan, Simon A. (2024). Rapid assessment of the blood-feeding histories of wild-caught malaria mosquitoes using mid-infrared spectroscopy and machine learning. Malaria Journal, 23 (1) 86, 86. doi: 10.1186/s12936-024-04915-0
2024
Journal Article
Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning
Sikulu-Lord, Maggy T., Edstein, Michael D., Goh, Brendon, Lord, Anton R., Travis, Jye A., Dowell, Floyd E., Birrell, Geoffrey W. and Chavchich, Marina (2024). Rapid and non-invasive detection of malaria parasites using near-infrared spectroscopy and machine learning. PLoS One, 19 (3) e0289232, 1-18. doi: 10.1371/journal.pone.0289232
2023
Journal Article
Near-infrared spectroscopy and machine learning algorithms for rapid and non-invasive detection of Trichuris
Kariyawasam, Tharanga N., Ciocchetta, Silvia, Visendi, Paul, Soares Magalhães, Ricardo J., Smith, Maxine E., Giacomin, Paul R. and Sikulu-Lord, Maggy T. (2023). Near-infrared spectroscopy and machine learning algorithms for rapid and non-invasive detection of Trichuris. PLOS Neglected Tropical Diseases, 17 (11) e0011695, e0011695. doi: 10.1371/journal.pntd.0011695
2023
Journal Article
Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis
Mshani, Issa H., Siria, Doreen J., Mwanga, Emmanuel P., Sow, Bazoumana Bd., Sanou, Roger, Opiyo, Mercy, Sikulu-Lord, Maggy T., Ferguson, Heather M., Diabate, Abdoulaye, Wynne, Klaas, González-Jiménez, Mario, Baldini, Francesco, Babayan, Simon A. and Okumu, Fredros (2023). Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis. Malaria Journal, 22 (1) 346. doi: 10.1186/s12936-023-04780-3
2023
Other Outputs
Machine learning and detection of Trichuris muris in mice
Kariyawasam, Tharanga, Lord, Maggy and Ciocchetta, Silvia (2023). Machine learning and detection of Trichuris muris in mice. The University of Queensland. (Dataset) doi: 10.48610/7f11f9f
2023
Journal Article
Rapid and non-invasive detection of Aedes aegypti co-infected with Zika and dengue viruses using near infrared spectroscopy
Garcia, Gabriela A., Lord, Anton R., Santos, Lilha M. B., Kariyawasam, Tharanga N., David, Mariana R., Couto-Lima, Dinair, Tátila-Ferreira, Aline, Pavan, Márcio G., Sikulu-Lord, Maggy T. and Maciel-de-Freitas, Rafael (2023). Rapid and non-invasive detection of Aedes aegypti co-infected with Zika and dengue viruses using near infrared spectroscopy. Viruses, 15 (1) 11, 11. doi: 10.3390/v15010011
2023
Journal Article
State of the art and the future of fecal analysis using infrared spectroscopy
Kho, Elise A., Fernandes, Jill N., Tilbrook, Alan J., Fox, Glen P., Sikulu-Lord, Maggy T., Kotze, Andrew C., Beasley, Anne M., James, Peter J., Tolleson, Douglas R. and Cozzolino, Daniel (2023). State of the art and the future of fecal analysis using infrared spectroscopy. Applied Spectroscopy Reviews, 58 (10), 755-785. doi: 10.1080/05704928.2022.2143795
2023
Other Outputs
Spectral Data for Plasmodium
Lord, Maggy (2023). Spectral Data for Plasmodium. The University of Queensland. (Dataset) doi: 10.48610/5ecd1e8
2022
Other Outputs
Infrared signtures collected non-invasively from malaria positive and negative indviduals in Brazil
Kariyawasam Haputhanthri Kankanamge, Tharanga and Lord, Maggy (2022). Infrared signtures collected non-invasively from malaria positive and negative indviduals in Brazil. The University of Queensland. (Dataset) doi: 10.48610/e19e6fc
2022
Conference Publication
In vitro detection of dengue 1 virus in human whole blood, plasma, and serum with nearinfrared spectroscopy
Goh, Brendon, Visendi, Paul, Ciocchetta, Silvia, Soares, Ricardo, Liu, Wenjun and Lord, Maggy (2022). In vitro detection of dengue 1 virus in human whole blood, plasma, and serum with nearinfrared spectroscopy. American Society of Tropical Medicine and Hygiene 2022 Annual Meeting, Seattle, WA, United States, October 30 - November 3, 2022. Arlington, VA United States: American Society of Tropical Medicine and Hygiene.
2022
Journal Article
Malaria absorption peaks acquired through the skin of patients with infrared light can detect patients with varying parasitemia
Garcia, Gabriela A., Kariyawasam, Tharanga N., Lord, Anton R., da Costa, Cristiano Fernandes, Chaves, Lana Bitencourt, Lima-Junior, Josué da Costa, Maciel-de-Freitas, Rafael and Sikulu-Lord, Maggy T. (2022). Malaria absorption peaks acquired through the skin of patients with infrared light can detect patients with varying parasitemia. PNAS Nexus, 1 (5) pgac272, pgac272. doi: 10.1093/pnasnexus/pgac272
2022
Conference Publication
Novel diagnostic tools for soil transmitted helminths with non-invasive capability. The nearinfrared spectroscopy and artificial intelligence
Sikulu-Lord, Maggy T., Kariyawasam, Tharanga, Ciocchetta, Silvia, Soares Magalhaes, Ricardo J. and Giacomin, Paul (2022). Novel diagnostic tools for soil transmitted helminths with non-invasive capability. The nearinfrared spectroscopy and artificial intelligence. American Society of Tropical Medicine and Hygiene 2022 Annual Meeting, Seattle, WA, United States, October 30 - November 3, 2022. Arlington, VA United States: American Society of Tropical Medicine and Hygiene.
2022
Journal Article
First report of the detection of DENV1 in human blood plasma with near-infrared spectroscopy
Goh, Brendon, Visendi, Paul, Lord, Anton R., Ciocchetta, Silvia, Liu, Wenjun and Sikulu-Lord, Maggy T. (2022). First report of the detection of DENV1 in human blood plasma with near-infrared spectroscopy. Viruses, 14 (10) 2248, 2248. doi: 10.3390/v14102248
2022
Journal Article
Near-infrared spectroscopy as a feasible method for the differentiation of Neisseria gonorrhoeae from Neisseria commensals and antimicrobial resistant from susceptible gonococcal strains
Alharbi, Bushra, Cozzolino, Daniel, Sikulu-Lord, Maggy, Whiley, David and Trembizki, Ella (2022). Near-infrared spectroscopy as a feasible method for the differentiation of Neisseria gonorrhoeae from Neisseria commensals and antimicrobial resistant from susceptible gonococcal strains. Journal of Microbiological Methods, 201 106576, 106576. doi: 10.1016/j.mimet.2022.106576
2022
Book Chapter
Application of infrared techniques for characterisation of vector-borne disease vectors
Sikulu-Lord, Maggy and Maciel-de-Freitas, Rafael (2022). Application of infrared techniques for characterisation of vector-borne disease vectors. Infrared Spectroscopy - Perspectives and Applications [Working Title]. (pp. 1-19) edited by Marwa El-Azazy, Khalid Al-Saad and Ahmed S. El-Shafie. London, United Kingdom: IntechOpen. doi: 10.5772/intechopen.106941
2021
Journal Article
Near infrared spectroscopy accurately detects Trypanosoma cruzi non-destructively in midguts, rectum and excreta samples of Triatoma infestans
Tátila-Ferreira, Aline, Garcia, Gabriela A., dos Santos, Lilha M. B., Pavan, Márcio G., de C. Moreira, Carlos José, Victoriano, Juliana C., da Silva-Junior, Renato, dos Santos-Mallet, Jacenir R., Verly, Thaiane, Britto, Constança, Sikulu-Lord, Maggy T. and Maciel-de-Freitas, Rafael (2021). Near infrared spectroscopy accurately detects Trypanosoma cruzi non-destructively in midguts, rectum and excreta samples of Triatoma infestans. Scientific Reports, 11 (1) 23884, 23884. doi: 10.1038/s41598-021-03465-8
2021
Conference Publication
The near-infrared spectroscopy technique can non-invasively detect malaria parasites through the skin of mice
Sikulu-Lord, Maggy, Lord, Anton Richard, Goh, Brendon, Travis, Jye, Birrell, Geoffrey W., Chavchich, Marina, Harris, Ivor E., Mcleod-Robertson, Stephen, Kent, Anthony, Vanbreda, Karin and Edstein, Michael D. (2021). The near-infrared spectroscopy technique can non-invasively detect malaria parasites through the skin of mice. ASTMH Annual Meeting, Virtual, 17-21 November 2021. Deerfield, IL, United States: American Society of Tropical Medicine and Hygiene. doi: 10.4269/ajtmh.abstract2021
2021
Journal Article
The application of spectroscopy techniques for diagnosis of malaria parasites and arboviruses and surveillance of mosquito vectors: A systematic review and critical appraisal of evidence
Goh, Brendon, Ching, Koek, Soares Magalhães, Ricardo J., Ciocchetta, Silvia, Edstein, Michael D., Maciel-de-Freitas, Rafael and Sikulu-Lord, Maggy T. (2021). The application of spectroscopy techniques for diagnosis of malaria parasites and arboviruses and surveillance of mosquito vectors: A systematic review and critical appraisal of evidence. PLoS Neglected Tropical Diseases, 15 (4) e0009218, 1-24. doi: 10.1371/journal.pntd.0009218
2021
Journal Article
High throughput estimates of Wolbachia, Zika and chikungunya infection in Aedes aegypti by near-infrared spectroscopy to improve arbovirus surveillance
Santos, Lilha M. B., Mutsaers, Mathijs, Garcia, Gabriela A., David, Mariana R., Pavan, Marcio G., Petersen, Martha T., Correa-Antonio, Jessica, Couto-Lima, Dinair, Maes, Louis, Dowell, Floyd, Lord, Anton, Sikulu-Lord, Maggy and Maciel-de-Freitas, Rafael (2021). High throughput estimates of Wolbachia, Zika and chikungunya infection in Aedes aegypti by near-infrared spectroscopy to improve arbovirus surveillance. Communications Biology, 4 (1) 67, 67. doi: 10.1038/s42003-020-01601-0
Funding
Current funding
Past funding
Supervision
Availability
- Dr Maggy Lord is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Available projects
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Analysis of mosquitoes with Near-infrared and machine learning algorithms
This PhD project aims to assess the role of NIR and machine learning techniques to detect Ross River virus and blood meal status in mosquitoes. It requires insect handling/rearing knowledge, PCR techniques and machine learning. Both international and domestic students are encouraged to apply. When inquiring about this project, please let me know if you intent to apply for a scholarship. You should also use PhD project on Ross River virus in your title/subject line
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Comparative evaluation of handheld and benchtop NIR instruments for mosquito analysis
This project aims to compare the accuracy of smaller handheld NIR instruments with benchtop instruments for mosquito characterisation in the lab and field. It requires knowledge in insect handling/rearing, PCR techniques and machine leraning. Both international and domestic students are encouraged to apply. When inquiring about this project, please let me know if you intent to apply for a scholarship.
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Machine learning algorithms for insect characterisation using infrared data
The Lord Lab has been collecting infrared data on mosquito characterisation for >10 years. This PhD project is a dry lab only and aims to analyse these data with various machine learning algorithms to develop robust predictive models for global use. Both domestic and international students are encouraged to apply.
Supervision history
Completed supervision
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2024
Doctor Philosophy
Detection of malaria and arboviruses with spectroscopy and machine learning techniques
Principal Advisor
Other advisors: Professor Ricardo Soares Magalhaes, Dr Silvia Ciocchetta
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2024
Doctor Philosophy
Exploring diagnostic approaches and quality assurance data for improved management of gonorrhoea antimicrobial resistance
Associate Advisor
Other advisors: Associate Professor David Whiley, Dr Emma Sweeney, Dr Ella Trembizki
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2021
Doctor Philosophy
Detecting Haemonchus contortus infection in sheep using infrared spectroscopy
Associate Advisor
Other advisors: Adjunct Professor Andrew Kotze, Dr Anne Beasley
Media
Enquiries
Contact Dr Maggy Lord directly for media enquiries about:
- infrared spectroscopy
- malaria
- Mosquitoes
- non-invasive diagnostic tools
- surveillance
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