Aleksei Tiulpin, PhD
Post-doctoral fellowFinnish Center for Artificial Intelligence & Aalto University
Konemiehentie 2
02150 Espoo
Finland
Email: firstname [dot] lastname [at] aalto [dot] fi
Google Scholar
GitHub
Kaggle
About me
I am post-doctoral fellow at the Finnish Center for Artificial Intelligence and Aalto University working with Prof. Samuel Kaski and Prof. Simo Särkkä.
I am also a member of the European Lab for Learning and Intelligent Systems (ELLIS).
Previously, I was a post-doctoral fellow at KU Leuven, working with Prof. dr. Matthew Blaschko.
I earned my PhD during 2017-2020 (graduated with distinction) at the Faculty of Medicine, University of Oulu, Finland.
My PhD thesis was nominated the best doctoral thesis of the year 2020. My advisors were
Prof. Simo Saarakkala, PhD (primary),
Dr. Jérôme Thevenot, PhD,
and Prof. Esa Rahtu.
In addition to my academic activities, I am a co-founder and CTO of Ailean Technologies Ltd.
Research interests
I am currently working on AI-assisted design in the context of medical aplications. Generally, I am interested in Bayesian methods,
semi-supervised, self-supervised, and active learning. My main application area is medical imaging.
My translational contributions are in the fields of on musculoskeletal disorders, breast cancer, and dementia.
My research agenda is to investigate how to build medical AI systems that
- Are multimodal
- Use as little labeled data as possible
- Predict how uncertain they are in their predictions
- Interact with humans and other AI systems
Current PhD students
I am privelleged to supervise the following PhD students at the University of Oulu:
- Egor Panfilov, MSc, 2022 (w. prof. Simo Saarakkala and prof. Miika Nieminen)
- Huy Hoang Nguyen, MSc, 2023 (w. prof. Simo Saarakkala and prof. Matthew Blaschko)
- Abu Mohammed Raisuddin, MSc, 2024 (w. prof. Osmo Tervonen),
- Santeri Rytky, MSc, 2024, (w. prof. Jaakko Niinimäki and prof. Simo Saarakkala)
- Terence McSweeney, MSc, 2024 (w. Prof. Simo Saarakkala and prof. Jaro Karppinen)
- Elias Vaattovaara, MD, 2025 (w. docent Mika Nevalainen and prof. Simo Saarakkala)
Publications
I have over 20 published / in press international peer-reviewed papers. I also have several patents.
My PhD thesis: Download PDF.
Tiulpin A. & Blaschko M.B (2021) Greedy Bayesian Posterior Approximation with Deep Ensembles.
arXiv preprint arXiv:2105.14275
[Link] [Code]
Nguyen, H. H., Saarakkala, S., Blaschko, M. B., & Tiulpin, A. (2021).
DeepProg: A Transformer-based Framework for Predicting Disease Prognosis. arXiv preprint arXiv:2104.03642.
[Link]
Raisuddin, A. M., Vaattovaara, E., Nevalainen, M., Nikki, M., Järvenpää, E., Makkonen, K., ... & Tiulpin, A. (2020).
Critical Evaluation of Deep Neural Networks for Wrist Fracture Detection. Scientific reports, 11(1), 1-11.
[Link] [Code]
Nguyen, H. H., Saarakkala, S., Blaschko, M. B., & Tiulpin, A. (2020).
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading From Plain Radiographs.
IEEE transactions on medical imaging, 39(12), 4346–4356.
[Link] [Code]
Tiulpin, A., Melekhov, I., & Saarakkala, S. (2019).
KNEEL: knee anatomical landmark localization using hourglass networks.
In Proceedings of the IEEE International Conference on Computer Vision Workshops (pp. 352-361)
[Link] [Code]
Tiulpin, A., Klein, S., Bierma-Zeinstra, S. M., Thevenot, J., Rahtu, E., van Meurs, J., Oei, E. & Saarakkala, S. (2019).
Multimodal machine learning-based knee osteoarthritis progression prediction from plain radiographs and clinical data.
Scientific reports, 9(1), 1-11.
[Link] [Code]
Tiulpin, A., Thevenot, J., Rahtu, E., Lehenkari, P., & Saarakkala, S. (2018).
Automatic knee osteoarthritis diagnosis from plain radiographs: a deep learning-based approach.
Scientific reports, 8(1), 1-10.
[Link] [Code]
