STAFF PROFILE
Professor Karin Verspoor
Position:
Dean, School of Computing Technologies
College / Portfolio:
STEM College
Phone:
+61399255654
Email:
karin.verspoor@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision
Professor Karin Verspoor is Dean of the School of Computing Technologies at RMIT University in Melbourne, Australia.
Karin's research primarily focuses on the use of artificial intelligence methods to enable biological discovery and clinical decision support, through extraction of information from clinical texts and the biomedical literature and machine learning-based modelling.
Karin held previous posts as Director of Health Technologies and Deputy Head of the School of Computing and Information Systems at the University of Melbourne, as the Scientific Director of Health and Life Sciences at NICTA Victoria Research Laboratory, at the University of Colorado School of Medicine, and at Los Alamos National Laboratory.
She is also the Victorian Node lead and co-founder of the Australian Alliance for Artificial Intelligence in Health.
- Artificial Intelligence in Medicine
- Biomedical Natural Language Processing
- Computational Linguistics
- Health Informatics
- Health Data Analytics
- Computational Biology
- Cheminformatics
- PhD, Cognitive Science and Natural Language, The University of Edinburgh (UK)
- MSc, Cognitive Science and Natural Language, The University of Edinburgh (UK)
- BA, Computer Science, Rice University (Houston, TX, USA)
- Intelligenesis/Webmind Corporation (New York, NY, USA)
- Applied Semantics (Los Angeles, CA, USA)
- Los Alamos National Laboratory (Los Alamos, NM, USA)
- National ICT Australia (Melbourne, VIC, Australia)
- Liu, Y.,Teo, S.,Meric, G.,Tang, H.,Verspoor, K., et al, . (2023). The gut microbiome is a significant risk factor for future chronic lung disease In: Journal of Allergy and Clinical Immunology, 151, 943 - 952
- Šuster, S.,Baldwin, T.,Lau, J.,Jimeno Yepes, A.,Iraola, D.,Otmakhova, Y.,Verspoor, C. (2023). Automating Quality Assessment of Medical Evidence in Systematic Reviews: Model Development and Validation Study In: Journal of medical Internet research, 25, 1 - 20
- Rozova, V.,Khanina, A.,Teng, J.,Teh, J.,Worth, L.,Slavin, M.,Thursky, K.,Verspoor, C. (2023). Detecting evidence of invasive fungal infections in cytology and histopathology reports enriched with concept-level annotations In: Journal of Biomedical Informatics, 139, 1 - 9
- Jimeno Yepes, A.,Verspoor, C. (2023). Classifying literature mentions of biological pathogens as experimentally studied using natural language processing In: Journal of Biomedical Semantics, 14, 1 - 14
- El-Hayek, C.,Barzegar, S.,Faux, N.,Doyle, K.,Verspoor, K., et al, . (2023). An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice In: International Journal of Medical Informatics, 173, 1 - 9
- Cao, K.,Verspoor, C.,Chan, E.,Daniell, M.,Sahebjada, S.,Baird, P. (2023). Stratification of keratoconus progression using unsupervised machine learning analysis of tomographical parameters In: Intelligence-Based Medicine, 7, 1 - 8
- Suster, S.,Baldwin, T.,Verspoor, C. (2023). Analysis of predictive performance and reliability of classifiers for quality assessment of medical evidence revealed important variation by medical area In: Journal of Clinical Epidemiology, 159, 58 - 69
- Pu, Y.,Beck, D.,Verspoor, K. (2023). Graph embedding-based link prediction for literature-based discovery in Alzheimer's Disease In: Journal of Biomedical Informatics, 145, 1 - 13
- Liu, J.,Capurro, D.,Nguyen, A.,Verspoor, K. (2023). Attention-based multimodal fusion with contrast for robust clinical prediction in the face of missing modalities In: Journal of Biomedical Informatics, 145, 1 - 13
- Otmakhova, Y.,Verspoor, K.,Baldwin, T.,Jimeno Yepes, A.,Lau, J. (2022). M3: Multi-level dataset for Multi-document summarization of Medical studies In: Proceedings of the Findings of the Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 07/12/2022-11/12/2022
- Privacy-Preserving Collaborative Analytics on Sensitive Data. Funded by: ARC-Linkage Project from (2023 to 2026)
- Appropriate Antimicrobial Use: Scaling Surveillance Using Digital Health (MRFFRD000113) (externally led by the University of Melbourne). Funded by: MRFF - 2021 Research Data Infrastructure from (2022 to 2026)
- Improving patient outcomes through implementation of digital and diagnostic innovations for infections in cancer (Peter Mac led). Funded by: National Health and Medical Research Council Synergy Grants from (2022 to 2027)
- Technology Development for improved Clinical Trials prediction models (administered by Opyl Limited). Funded by: Innovation Connections grant - Cat 1 from (2022 to 2023)
- Using artificial intelligence and novel technology to detect and monitor corneal disease (administered by University of Melbourne). Funded by: National Health and Medical Research Council (NHMRC) Project Grants 2017 (for funding commencing in 2018) from (2021 to 2023)
1 Masters by Research Current Supervisions