Statistics, Artificial Intelligence, Econometrics, Machine Learning, Operations Research
My research interests are focused on Bayesian model selection, averaging, and automatic model configuration in complex regression contexts ranging from simple linear models to highly nonlinear Bayesian regressions and Neural Networks. In general, Bayesian statistics, both applied (survey data, epigenetic data, QTL studies) and methodological (MCMC, Variational inference, EM-like algorithms), are my fields of expertise. I am also interested in Weak Supervision in Machine Learning through mixture modelling. Read more about master projects with me here.
STK2130 - Modeling by Stochastic Processes (plenary sessions and exercises)
STK3100 - Introduction to generalized linear models (exercises)
STK4900 - Statistical methods and applications (plenary sessions and exercises)
STK2100 - Machine Learning and Statistical Methods for Prediction and Classification (lecturing)
August 2014 - August 2018
Faculty of Mathematics and Natural Sciences
Speciality: Statistics
Dissertation: "Bayesian model configuration, selection and averaging in complex regression contexts".
August 2012 - June 2014
Faculty of Economics, Informatics and Social Research.
Speciality: Operations Research
Research Thesis: "Evaluation of Supply Vessel schedules robustness with a posteriori improvements".
September 2008 - June 2013
Faculty of Applied Mathematics and Computer Science. Department of Mathematical Modelling and Data Analysis
Speciality: Economic Cybernetics (mathematical methods and computer-based modelling in economy).
Research Thesis: "Methods and tools of investment management in conditions of international diversifications"
Bayesian model selection: Bayesian model selection.
September 2018 - December 2020
Fundamental research in statistics and machine learning, publishing articles and working on projects involving the development of customized statistical and machine learning methodology in various applications for private and public sectors, acting as a reviewer in several highly ranked journals including the Scandinavian Journal of Statistics, Journal of the American Statistical Association and Scientific Reports and conferences including ACL and EMNLP.
August 2014 - August 2018
Bayesian variable selection and model averaging. Bayesian deep feature engineering. Applied research with Genetic and Epigenetic data (GWAS, EWAS, QTL mapping, etc.).
September 2011 - June 2012
Calculation of CVA and regulatory capital as well as full support, implementation and customisation services within the Analyst project. Compatibl's customers included some of the largest and most respected banks and hedge funds worldwide, including 4 dealers, 3 supranational, over 20 central banks, and 3 major financial technology vendors.