Bio: Konstantin Avrachenkov received his Master degree in Control Theory from St. Petersburg State Polytechnic University (1996), his Ph.D. degree in Mathematics from the University of South Australia (2000), and Habilitation from the University of Nice Sophia Antipolis (2010). Currently, he is a Director of Research at Inria Sophia Antipolis, France. He is an associate editor of Probability in the Engineering and Informational Sciences, Stochastic Models, ACM TOMPECS, IEEE Trans on Automatic Control, and on advisory boards of ACM POMACS and the International Journal of Performance Evaluation. Konstantin has co-authored two books, “Analytic Perturbation Theory and its Applications”, SIAM, 2013 and “Statistical Analysis of Networks”, and more than 200 articles. He has won 5 best paper awards. His main theoretical research interests are Markov chains, Markov decision processes, random graphs, and singular perturbations. He applies these methodological tools to the modelling and control of networks, and to design data mining and machine learning algorithms.

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Bio: Sofía S. Villar is a Professor and Group Leader at the MRC Biostatistics Unit, University of Cambridge, where she works on efficient and innovative study design. Her research lies at the intersection of statistics, stochastic optimisation, and machine learning, with a particular emphasis on adaptive and patient-centred clinical trials. She develops methods aimed at making trials faster and more efficient while improving the allocation of participants to better-performing treatments. Sofía obtained her PhD in Business Administration and Quantitative Methods from Universidad Carlos III de Madrid, specialising in stochastic dynamic optimisation. In 2012, she was a postdoctoral researcher at BCAM-Basque Center for Applied Mathematics. Then, she joined the MRC Biostatistics Unit and, in 2014, became the first recipient of the Biometrika Postdoctoral Fellowship. She also contributes to national clinical trials and promotes the practical implementation of innovative adaptive designs in medical research and mobile-health applications.

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Bio: Michel Mandjes is a leading scholar in probability, operations research, and applied stochastic modelling. He earned M.Sc. degrees in mathematics and econometrics from the Free University of Amsterdam and completed his Ph.D. in operations research in 1996. After research positions at KPN Research and Bell Laboratories, he held senior academic and leadership roles at the University of Twente and CWI. He currently serves as full professor at both Leiden University and the University of Amsterdam and is affiliated with EURANDOM and the Institute for Advanced Study.His research focuses on stochastic processes, queueing theory, simulation methods, and the probabilistic analysis of complex networks, with applications spanning communication and transportation systems, healthcare, actuarial science, sociology, and biology. Mandjes has authored three books and published more than 350 scientific papers. He has played prominent leadership roles in the international research community, serving as program chair of major conferences and as Editor-in-Chief of Queueing Systems.

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