Dr Evangelos MitsokapasPostdoctoral ResearcherEmail: e.mitsokapas@qmul.ac.uk & evangelos@mitsokapas.grRoom Number: Mathematical Sciences Building, Room: MB-202 Office Hours: Please contact me by email for an appointment.ProfileTeachingPublicationsProfile Evangelos Ch. Mitsokapas completed his PhD studies at the Dynamical Systems and Statistical Physics Group, under the supervision of Dr. Rosemary J. Harris, at the School of Mathematical Sciences at Queen Mary University of London. His research topics lie within the field of Statistical Mechanics, non-extensive complex systems and the behavioural study of systems exhibiting non-markovian dynamics. His approach includes extreme-value memory modelling under the concept of peak-end rule, as well as developing applications in modelling collective behaviour in real systems with memory. Evangelos obtained his postgraduate Diploma (MSc) on Applied Mathematics in 2016, from University of Patras, Greece, where he completed his thesis, entitled: "Statistical Mechanics and Entropy of Complex Systems". The purpose of his study was the introduction of the so-called Non-Extensive Statistical Mechanics, which could provide a more accurate macroscopic description regarding the chaotic behaviour of Hamiltonian systems of non-linear oscillators, that cannot be described by the classical approach of Boltzmann-Gibbs Statistical Mechanics. After completing his postgraduate studies, he was invited for a short period of time to Nazarbayev University of Astana, Kazakhstan, to work on the numerical simulation of the dynamics of complex systems. On 2022 Evangelos obtained the Qualified Teacher Status from the Department for Education of the United Kingdom. TeachingSince 2017 Evangelos has taught several modules at Queen Mary University of London, targeted at both the UG and PG curriculums. As a Teaching Associate (TA), he has worked for various schools of Queen Mary University of London, including the School of Mathematical Sciences, School of Biological and Chemical Sciences as well as the School of Engineering and Material Sciences. During the academic year 2020-2021, Evangelos has been delivering additional classes on Dynamical systems and advanced Probability and Inference Statistics at King's College London, for UG students at the Department of Mathematics.Undergraduate TeachingQueen Mary University of London - School of Mathematical Sciences (2017-2022): Teaching Associate Introduction to Python and Computer Programming Probability and Statistics I (IT Class) Statistical Modeling I (R-based Tutorial) Differential Equations Discrete Mathematics Probability Models Introduction to Algebra Demonstrator Calculus III Partial Differential Equations - School of Biological and Chemical Sciences (2018-2019): Teaching Associate Mathematics I (Foundation) Mathematics II - School of Engineering and Materials Science (2018-2019): Chemical Reaction Engineering (Maple-based Tutorial) King's College London - Department of Mathematics (2020-2021): Graduate Teaching Associate Probability and Statistics I Probability And Statistics II Introduction to Dynamical Systems (Mathematica-based) Postgraduate TeachingQueen Mary University of London School of Mathematical Sciences (2020-2021): Teaching Associate Foundations of Mathematical Modelling in Finance Programming for Business Analytics ResearchPublications Mitsokapas, E. (2022). Statistical Mechanics Modelling of Human Experiences: Memory and Delays (Doctoral dissertation, Queen Mary University of London). Mitsokapas, E., & Harris, R. J. (2022). Decision-making with distorted memory: Escaping the trap of past experience. Physica A: Statistical Mechanics and its Applications, 593, 126762. Mitsokapas, E., Schäfer, B., Harris, R. J., & Beck, C. (2021). Statistical characterization of airplane delays. Scientific Reports, 11(1), 1-11. Moulos, Vrettos, et al. (2018). A robust information life cycle management framework for securing and governing critical infrastructure systems. Inventions 3.4: 71.