معرفی
O. Deniz Akyildiz is an Assistant Professor in Statistics at the Department of Mathematics, Imperial College London. His research focuses on computational statistics, machine learning, and generative modelling, with applications to sampling, optimization, and inverse problems. He holds affiliations with the Artificial Intelligence Network and Mathematics research groups. Previously, he obtained degrees in Electronics and Communications Engineering from İTÜ, followed by a PhD in Signal Processing at Universidad Carlos III de Madrid. Before joining Imperial, he worked as a postdoctoral researcher at Warwick CS and The Alan Turing Institute.
His research interests span diffusion-based parameter estimation, score-based generative models, Langevin dynamics for optimization, and adaptive importance samplers. Recent work includes contributions to latent diffusion models, Sinkhorn semigroups, and stochastic filtering techniques.
Notable publications include works on statistical finite elements, interacting particle Langevin algorithms, and physics-informed deep generative models. His technical blog almost stochastic and GitHub repository provide further insights into his research.
