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Dr. Jelena Fiosina

Dr. Jelena Fiosina   Address: Julius-Albert-Str. 4, Room 219
Phone: (+49) 5323-72-7151

Jelena Fiosina received her Master degree in Computer Sciences from Riga Technical University (RTU) in 2002. She obtained her Ph.D. in Telematics and logistics (in the field of Statistics) with the title “The estimation of Transport Logistic processes models on the base of intensive computer methods of statistics” from TTI in 2006.

During the time of her doctoral studies (2002-2006) she worked as assistant, lecturer and researcher in TTI in the department of Mathematical methods and modelling. After obtaining Ph.D. (2006-2009) she continued her academic and research career in RTU in the Department of mathematical methods of transport systems control.

Her teaching experience includes such courses as introduction to stochastic processes; probability theory and mathematical statistics; discrete mathematics; computational processes and structures theoretical fundamentals; queuing theory; traffic flow theory; modelling and simulation of transport systems; computer statistics for transport system analysis and others. She conducted research in a number of Latvian research projects, connected with mathematical methods and software development for optimisation of transport system network of Latvia”.

Her research interests include: applied, mathematical and computational statistics, stochastic processes and models, operations research, simulation, artificial and computational intelligence, and application of those methods and models in transport, transportation, logistics and reliability domains.

The results of her research are reflected in about 20 publications in international conference proceedings and journals, among them: Journal of Statistical Planning and Inference, Journal of Quality Technology and Quantitative Management, Communications in Dependability and Quality Management.

Jelena joined the MEC research group in June 2011, obtaining FP7 Marie Curie Actions IEF fellowship for the project ADMIT (Agent-oriented Distributed Data Mining using Computational Statistics).

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