Aapo Peräkorpi

DC3 – Data-driven, adaptive, machine learning approaches for multispectral DOT

About Aapo

Aapo successfully completed his Master of Science in Physics from the University of Eastern Finland in 2023, with a specialisation in Applied Physics and a track in computational physics. Prior to this, he obtained his Bachelor of Science in Physics in 2021 from the same institution, focusing on Applied Physics.

Throughout his academic journey, he has developed a profound interest in the intersection of artificial intelligence/machine learning, inverse problems, and their diverse applications. This enthusiasm led him to undertake a year-long internship at the Finnish Meteorological Institute from 2022 to 2023, where he gained practical experience and further honed his skills in his areas of interest.

“I am passionate about bridging the realms of physics and machine learning in diffuse optical tomography. Joining the CONcISE network excites me as it offers a unique platform to collaborate, innovate, and unravel the mysteries of biomedical imaging for a brighter, healthier future.” – Aapo Peräkorpi (DC3).

About the research programme

Aapo’s PhD programme is centred on advancing image reconstruction in diffuse optical tomography by leveraging deep learning techniques on compressed data. It also explores the development of adaptive, data-driven methods for image reconstruction, aiming to optimise accuracy and efficiency in the process. Apoo is carrying out his research at DATRIX in Milan, Italy. Two secondments are planned throughout his emplyoment.

Main employer

Secondment 1

Secondment 2

Main employer

Secondment 1

Secondment 2

Funded by the European Union (GA 101072354). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

UK participants are funded by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (grant number EP/X030733/1).