CV

Education

• Ph.D (ongoing) in Machine Learning Applied to Medicine, Aix-Marseille University, 2024 (expected)
• M.S. in Computer Science and Machine Learning, Aix-Marseille University, 2021
• B.S. in Computer Science, Aix-Marseille University, 2019

Work experience

• 2021-2024: PhD Student in Artificial Intelligence Applied to Medicine
  • Laboratoire Informatique et Systèmes, Aix-Marseille University
  • Similarity Learning Approaches for Assisting Melanoma Diagnosis
  • Supervisors: Professors D. Merad and S. Dubuisson
• Summer 2020: Research Intern
  • Laboratoire Informatique et Systèmes, Aix-Marseille University
  • Preliminary work on machine learning interpretability and skin lesions asymmetry
  • Supervisor: Professor R. Iguernaissi

Skills

• Designing and deploying cutting-edge machine learning models for research
  • Python
  • Docker
  • Git
  • Pytorch
  • Tensorflow / Keras
• Scientific Writing
  • Latex
  • Zotero
• Software development
  • C/C++, C#, Java
  • Object-Oriented programming
  • Gtk+
  • Qt
• Videogame development
  • Unity
  • Unreal Engine
• Android App Development
  • Android Studio

Publications

Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions

A. C. Foahom Gouabou, J. Collenne, J. Monnier, R. Iguernaissi, J.-L. Damoiseaux, A. Moudafi, D. Merad."Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions." International Journal of Molecular Sciences. 2022; 23(22)

Enhancing Anomaly Detection in Melanoma Diagnosis Through Self-Supervised Training and Lesion Comparison

J. Collenne, R. Iguernaissi, S. Dubuisson, D. Merad (2024). "Enhancing Anomaly Detection in Melanoma Diagnosis Through Self-Supervised Training and Lesion Comparison." Machine Learning in Medical Imaging. MLMI 2023. Vancouver, BC, Canada.

Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection

J. Collenne, J. Monnier, R. Iguernaissi, M. Nawaf, M.-A. Richard, J.-J. Grob, C. Gaudy-Marqueste, S. Dubuisson, D. Merad. (2024). "Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection." Journal of Investigative Dermatology.

Automated melanoma detection. An algorithm inspired from human intelligence characterizing disordered pattern of melanocytic lesions improving a convolutional neural network.

J. Monnier, A. C. Foahom Gouabou, M. Serdi, J. Collenne, R. Iguernaissi, M.-A. Richard, C. Gaudy-Marqueste, J.-L. Damoiseaux, J.-J. Grob, D. Merad. (2024). "Automated melanoma detection. An algorithm inspired from human intelligence characterizing disordered pattern of melanocytic lesions improving a convolutional neural network." Journal of the American Academy of Dermatology.

ReSet: A Residual Set-Transformer approach to tackle the ugly-duckling sign in melanoma detection

J. Collenne, R. Iguernaissi, S. Dubuisson, D. Merad (2024). "ReSet: A Residual Set-Transformer approach to tackle the ugly-duckling sign in melanoma detection." International Conference on Image Processing. ICIP 2024. Abu Dhabi, UAE.

Teaching

Communication

Data Sources with SQL

Web development