معرفی
Adrien BIBAL holds a Doctor of Sciences degree and is actively engaged in research at the intersection of Machine Learning, Dimensionality Reduction, and Data Visualization. His work emphasizes model interpretability, constraint integration, and physics-informed algorithms, with applications in radiation oncology and nonlinear dimensionality reduction.
- Education:
- Bachelor's in Computer Science (UCL, 2011)
- Master's in Computer Science (UCL, 2013)
- Master's in Philosophy (UCL, 2015)
His research includes advancements in embedding quality assessment, rotational invariance in neural networks, and clinical AI implementation. Key projects like VeriLearn (2018–2022) highlight his focus on verifying artificial intelligence systems. Collaborations span interdisciplinary domains, including physics, clinical medicine, and stochastic processes.
Keywords from his work include Machine Learning, Data-Model Dependency, Rotational Invariance, Physics-Informed ML, and Embedding Quality. He has published in venues such as IEEE Transactions on Visualization and Computer Graphics, NeurIPS, and Physics in Medicine and Biology.
