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Ioannis Tsamardinos main research concerns three directions (a) the development of novel, state-of-the-art algorithms and theory for Machine Learning, Bayesian Network learning, Variable Selection, and Causal Discovery; the methods are inspired by data analysis problems in biomedicine, (b) application of state-of-the-art data analysis methods in biomedical data to discover new domain knowledge, and (c) the development of automated systems for facilitating data analysis for non-expert users. Prof. Tsamardinos has over 60 publications in international journals, conferences, and books. He has also participated in several applied projects (including US and EU funded projects) to biomedicine,...

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