Skip to content
View tnadiedjoa's full-sized avatar
8 followers · 14 following

Highlights

  • Pro

Block or report tnadiedjoa

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
tnadiedjoa/README.md

Théophile Nadiedjoa

Engineering student on a gap year, focused on Artificial Intelligence and Computer Vision

  • I'm an engineering student at Télécom Paris (Institut Polytechnique de Paris), with two majors: Signal Processing for Artificial Intelligence and Computer Vision
  • During my gap year, I'm an AI Research Intern in the Prediction Team at SkillCorner, working on deep learning for spatio-temporal data and uncertainty estimation
  • My interests are representation learning and generative models, label-efficient learning from weak or noisy supervision, and rigorous evaluation of deep models, with a particular pull towards computer vision applied to biomedical imaging
  • Currently looking for a 6-month internship, February to August 2027
  • How to reach me: theophile.nadiedjoa@telecom-paris.fr
  • How to connect with me: linkedin.com/in/theophile-nadiedjoa

Majors

Signal Processing for Artificial Intelligence: signal representations, time series, statistics and linear models, optimization, machine learning, deep learning, NLP, music and speech analysis

Computer Vision: image processing, medical and biological imaging, 3D vision and video, variational and Bayesian methods, generative models, deep learning for object recognition, classification and segmentation

Pinned Loading

  1. MEDVAE-X MEDVAE-X Public

    Forked from yrothlin-03/MEDVAE-X

    Study of MedVAE on coronary angiography (ARCADE): robustness, FiLM quality conditioning, JEPA adaptation, latent segmentation. Revised with 3 seeds and control baselines.

    Jupyter Notebook

  2. White-Blood-Cell-Classification-Kaggle White-Blood-Cell-Classification-Kaggle Public

    Classical ML and deep learning pipelines for white blood cell classification (13 classes): in-class Kaggle challenge, Télécom Paris IMA205.

    Jupyter Notebook

  3. Rating-UFC Rating-UFC Public

    Ranks UFC fighters with a leakage-free fight-outcome model and a virtual round-robin, backtested against the official rankings since 2013.

    Jupyter Notebook

  4. Dermoscopic-Lesion-Segmentation Dermoscopic-Lesion-Segmentation Public

    Classical computer vision (no deep learning) for skin lesion segmentation on ISIC dermoscopic images: two published methods reimplemented plus our own multi-channel Otsu baseline, with a convex-hul…

    Jupyter Notebook