Iosif lytras

Iosif's research interests include learning unknown distributions through sampling, Numerical Analysis of Stochastic Differential Equations and Optimization. Specifically, his research will focus on areas such as sampling with Langevin MCMC algorithms and generative diffusion models. Broader research interests include Concentration Inequalities, Random Matrix Theory and Mathematical Neuroscience and Classical Numerical Quadrature.


Iosif holds a PhD from the Department of Mathematics at the University of Edinburgh under the supervision of Professor Sotiris Sabanis. He has an undergraduate and a postgraduate degree from the Department of Mathematics of the NKUA. He has research experience around Langevin Monte Carlo algorithms and their applications in optimization and neural networks. His research has mainly focused on sampling from distributions where the log-gradient grows super-linearly. He has participated in the teaching of many undergraduate and postgraduate courses such as Probability, Infinite Calculus, Complex Analysis, Stochastic Analysis, Numerical Analysis of Differential Equations. He completed his 4-year undergraduate program in 3.5 years and graduated with honors in his undergraduate and graduate studies. During his PhD he was funded by the UK EPSRC throughout his studies.


The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

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