Miss Lana Tikhomirov
School of Computer Science and Information Technology
College of Engineering and Information Technology
Advancements in AI-based technologies far outpace research that inform us of their influence on human decision-making. As such, my work resides in the nascent field that combines AI safety, cognitive science, and bioethics research for development of complementary and safe AI technologies. Specifically, I investigate the impact of medical AI systems in clinical decision-making contexts and translational methodologies for AI in medicine. Further, I am interested in ethical and safe AI development to ensure fairness and accountability practices.
I completed by PhD in 2026 for my thesis entitled, 'What can cognitive science teach us about safe clinical decision-making with artificial intelligence?' supervised by Professor Carolyn Semmler (School of Psychology), Associate Professor Melissa McCradden (Australian Institute for Machine Learning, Women's and Children's Hospital) and Dr Lauren-Oakden Rayner.
Currently, I am a postdoctoral researcher in clinical AI safety and the Human factors and health policy lead at the Women's and Children's Hospital, Adelaide. I am based at the Australian Institute for Machine Learning.
Advancements in AI far outpace research that inform us of their cognitive and decisional influences on humans. Traditional research on human-computer interaction demonstrates the challenges of effective decision-making when combining these two fundamentally different entities. As such, my work resides in the nascent field that combines AI safety, cognitive science, and human factors research for development of effective decisional AI technologies. Specifically, I investigate the impact of medical AI systems from model development to implementation on clinical decision-making. Based at the Australian Institute for Machine Learning, my project is an interdisciplinary approach to the design and implementation of AI in high-risk settings. My research aims to inform human-computer interaction research from a cognitive science perspective and provide insight for industries in medical technology. Further, I am interested in ethical AI development to ensure fairness and accountability practices.
I am jointly supervised by Associate Professor Carolyn Semmler (School of Psychology) and Dr. Lauren Oakden-Rayner (School of Medicine/Australian Institute for Machine Learning).
| Date | Position | Institution name |
|---|---|---|
| 2022 - 2025 | PhD Candidate | University of Adelaide |
| Date | Institution name | Country | Title |
|---|---|---|---|
| Flinders University | Australia | Bachelor of Psychology (Honours) |
| Year | Citation |
|---|---|
| 2024 | Tikhomirov, L., Semmler, C., McCradden, M., Searston, R., Ghassemi, M., & Oakden-Rayner, L. (2024). Medical artificial intelligence for clinicians: the lost cognitive perspective. The Lancet: Digital Health, 6(8), e589-e594. Scopus40 WoS36 Europe PMC26 |
| 2023 | Tikhomirov, L., Bartlett, M. L., Duncan-Reid, J., & McCarley, J. S. (2023). Identifying inefficient strategies in automation-aided signal detection.. J Exp Psychol Appl, 29(4), 869-886. Scopus9 WoS8 Europe PMC3 |
| 2022 | Tikhomirov, L., Bartlett, M. L., Duncan-Reid, J., & McCarley, J. S. (2022). Identifying Inefficient Strategies in Automation-Aided Signal Detection. |
| - | Tikhomirov, L., Semmler, C., Prizant, N., Bhasin, S., Kenyon, G., van der Vegt, A., . . . McCradden, M. D. (2026). A scoping review of silent trials for medical artificial intelligence. Nature Health, 1(5), 532-554. |
| Year | Citation |
|---|---|
| 2026 | Tikhomirov, L., Semmler, C., Prizant, N., Bhasin, S., Kenyon, G., Van Der Vegt, A., . . . McCradden, M. (2026). A scoping review of silent trials for medical artificial intelligence. DOI |
| 2026 | Tikhomirov, L., Smith, L., Bird, A., Palmer, L., Kurian, N. C., & Semmler, C. (2026). What can reader studies of radiologist use of AI models teach us about adaptation? A signal detection modelling exploration. DOI |
| 2026 | Tikhomirov, L., Smith, L., Bird, A., Palmer, L., Kurian, N. C., & Semmler, C. (2026). What lies beneath performance gains? How cognitive modelling provides a compass for understanding changes to radiological decision-making with AI. DOI |
| 2026 | Tikhomirov, L., Smith, L., Bird, A., Palmer, L., Kurian, N. C., & Semmler, C. (2026). What lies beneath performance gains? How cognitive modelling provides a compass for understanding changes to radiological decision-making with AI. DOI |
| 2025 | Tikhomirov, L., Semmler, C., Prizant, N., Bhasin, S., Kenyon, G., Van Der Vegt, A., . . . McCradden, M. (2025). Opening the ‘black box’ of the silent phase evaluation for artificial intelligence: a scoping review and critical analysis. DOI |
| 2025 | Tikhomirov, L., Semmler, C., Prizant, N., Bhasin, S., Kenyon, G., Van Der Vegt, A., . . . McCradden, M. (2025). Opening the ‘black box’ of the silent phase evaluation for artificial intelligence: a scoping review and critical analysis. DOI |
| 2024 | Tikhomirov, L., Smith, L., Oakden-Rayner, L., Bird, A., Palmer, L., & Semmler, C. (2024). Large-Scale Evaluation of the Influence of AI-use on Radiologist Performance using Signal Detection Theory. DOI |
| 2024 | Tikhomirov, L., Smith, L., Bird, A., Palmer, L., Kurian, N. C., & Semmler, C. (2024). What can reader studies of radiologist use of AI models teach us about adaptation? A signal detection modelling exploration. DOI |
| 2023 | Tikhomirov, L., Semmler, C., & Searston, R. (2023). Medical AI for Radiology: The Lost Cognitive Perspective. DOI Europe PMC1 |