معرفی
O. Deniz Akyildiz is an Assistant Professor in Statistics at the Department of Mathematics, Imperial College London. He holds a PhD in Signal Processing from Universidad Carlos III de Madrid (UC3M) and completed postdoctoral work at Warwick CS and The Alan Turing Institute. His research bridges computational statistics, machine learning, and applied probability, focusing on stochastic sampling methods, generative modeling, and optimization techniques for statistical inference and inverse problems.
- Education: BSc/MSc in Electronics and Communications Engineering (İTÜ), PhD in Signal Processing (UC3M).
His work explores diffusion-based parameter estimation, score-energy-latent generative models, and overdamped/underdamped Langevin dynamics for probabilistic solutions to PDEs. He has developed adaptive importance samplers and contributed to high-dimensional stochastic filtering with real-world data.
Recent efforts include lecture notes and code for stochastic simulation courses and organizing workshops on Gradient Flows for Sampling (Royal Statistical Society, 2023) and Accelerating Generative Models (Alan Turing Institute, 2022-2023). His publications emphasize error bounds in diffusion models, physics-informed neural processes, and convergence analysis of optimization-driven sampling algorithms.
