Main publications
Robin Camarasa, Hoel Kervadec, Daniel Bos, Marleen de Bruijne (Talk)
Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, Eline Kooi, Aad van der Lugt, Marleen de Bruijne
Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, Eline Kooi, Aad van der Lugt, Marleen de Bruijne (Talk)
For the complete list of my publications, visit my Google scholar
Education
Ph.D. project focused on uncertainty and interpretability of Convolutional Neural Networks, applied to cardiovascular diseases.
Major in Data Science and Computer Science (Data Science, Web Programming, Big Data, Image Analysis, Parallel Computing, Artificial Intelligence)
2-year undergraduate intensive course in Physics, Algebra, Mathematics Analysis and Theoretical Computer Science
Positions
Teaching python to 60 master students. Creation of practicals, exams, and course resources. Correction of exams.
Collaboration on the international medical imaging challenge VALDO. Web development. Teaching of good programming practices (git, test driven development...)
Part of the administation team of a GPU cluster of 6 nodes (and 8 GPU per nodes). In charge of the module administration and the in-boarding of new members
6-month data sciences internship covering various type of projects from Business Intelligence to theoretical Machine Learning (Spiking Neural Networks) for customers
3-month internship. Participation to two international medical imaging challenges.
Projects
A 3 month (part-time) master project investigating Bayesian Deep Learning on MNIST dataset.
A 3 month (part-time) master computer science project applying AI algorithms to a nutritive coach in the form of an android application.
A 3 months (part-time) bachelor physics project of 3D object reconstruction after 2D scanning.
A 6 months (part-time) bachelor mathematic project demonstrating a practical manner to assess the quality of a card shuffle.