André Pedersen

Brattørkaia 17A

7010 Trondheim

Trøndelag, Norway

Hi! I’m a Senior Machine Learning Engineer at Sopra Steria. I have strong experience in using artificial intelligence and image analysis techniques for various medical applications, aiming to develop solutions that can assist clinicians in their daily practice. Currently, my main focus is on using generative AI and large multimodal models to solve various problems in the industry.

I was a MSc student at the Arctic University of Norway (UiT), from August 2014 to June 2019, in applied physics and mathematics, specializing in machine learning and statistics. I completed a summer internship at SINTEF Digital in 2018, which I ended up collaborating with on my Master’s thesis. From January 2019, I worked part-time at SINTEF while finishing my degree.

I started my PhD fellowship October 2019 in collaboration with the same research group as for my Master’s thesis. I was a PhD Candidate until 2023, where I published several papers on computational pathology, while I also held a position as a Research Scientist at the Medical Image Analysis group at SINTEF. I successfully defended my PhD November 2024.

In parallel to my PhD work, I have developed open, standalone software for C++ and Python, mainly using Qt5/PySide6 (e.g., FastPathology and Raidionics). I have published open command line tools (e.g., livermask), developed Python packages (e.g., gradient-accumulator, torchstain), and published articles to high-impact scientific journals related to medical image analysis and deep learning (on topics such as image classification, semantic segmentation, image-to-image registration, high-performance computing, semi-supervised learning, and natural language processing).

I have also written a book chapter and acted as a reviewer for scientific journals, such as Medical Image Analysis, Nature Scientific Reports, Frontiers in Medicine, IJCARS, QIMS, and BMC Medical Imaging. Lastly, I have (co-)supervised five Master’s students working on using deep learning for supervised/semi-supervised segmentation of 3D medical images (CT), multilabel histopathology image classification, and bronchoscopy video navigation.

news

Nov 15, 2024 Officially a Doctor! Successfully defended my PhD in Medical Technology!
Oct 2, 2024 AeroPath paper published in PLOS ONE (see here). Paper, annotated dataset, trained models, demo web app, and source code are all made openly available (see here).
May 12, 2024 Achieved a certification in Machine Learning in Production from DeepLearning.AI. See the certificate here.
Jan 23, 2024 Achieved the Microsoft Azure AI Engineer Associate Certificate. See the certificate here.
Jan 19, 2024 Achieved the Microsoft Azure Data Scientist Associate Certificate. See the certificate here.
Jan 7, 2024 Achieved a certification in Generative AI with Large Language Models from DeepLearning.AI. See the certificate here.

today's publication

  1. Comp.M.Bio
    Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding
    David Bouget,  André Pedersen, Johanna Vanel, Haakon O. Leira, and Thomas Langø
    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Mar 2022