- Research, consulting, development, and application of unique self-organising, inductive, statistical learning modelling and knowledge discovery technologies for more than 15 years. - Developer of the KnowledgeMiner Insights software package, a distinguished commercial self-organising modelling and knowledge extraction tool. It implements a unique and innovative set of parallel algorithms for modelling, validation, and workflow processing of complex, high-dimensional systems to allow knowledge extraction from noisy data in a most objective, automated, and fast way. - Development and implementation of a number of innovative algorithms for validation of inductively built models including new approaches for live numerical applicability domain evaluation, cost-sensitive and ensemble modelling with per-compound prediction uncertainty, and self-organising knowledge extraction from high-dimensional variables space of noisy data. - Areas of activity has been, for example: modelling and prediction of toxicological and eco-toxicological hazards and risks of chemical compounds for regulatory purposes, climate change related modelling and prediction problems, sales and demand predictions, macro- and micro-economic modelling problems like national economy and balance sheet prediction, energy consumption analysis and prediction, energy load forecasting, autoupdating wind energy generation forecast, medical diagnosis of diseases, and wastewater reuse problems.Specialties: self-learning, self-organizing, predictive modeling from noisy data, sales and demand forecasting, time series forecasting, knowledge discovery and data mining, cost-optimized modeling, modelling of complex systems