I am an Assistant Professor in Statistics at the Department of Mathematics, Imperial College London. Previously, I obtained my BSc and MSc in Electronics and Communications Engineering from İTÜ, completed my PhD in Madrid in Signal Processing, and worked as a postdoctoral research associate at Warwick CS and The Alan Turing Institute (within CoSInES) before joining Imperial.
My research is at the interface of computational statistics, machine learning, and applied probability - focusing on sampling, generative modelling, and optimisation. I develop stochastic and probabilistic mathematical machinery for statistical inference and machine learning. A few highlights are:
- diffusion-based parameter estimation in statistical models: multiscale, proximal, accelerated with applications to inverse problems
- score-based, energy-based, deep latent generative models for inverse problems
- nonconvex optimisation and sampling based on overdamped and underdamped Langevin dynamics with applications to probabilistic solutions of partial differential equations
- convex or nonconvex adaptive importance samplers
- high-dimensional stochastic filtering for unstructured (real-world) data
See works page for preprints, papers, slides, posters, and other things related to my work. I maintain a research blog called almost stochastic for short notes which might be of interest to other people.
If you are interested in joining for a PhD, please see this page.
Here are some more links: My Google Scholar, github, LinkedIn.