معرفی
Erik Štrumbelj is a researcher specializing in probability, statistics, and machine learning. His work focuses on stochastic processes, Monte Carlo methods, Bayesian statistics, and applications in sports analytics (player evaluation, match simulation, statistical forecasting). He has contributed to advancing computationally intensive statistical analysis and has collaborated on interdisciplinary projects involving data mining, high-performance computing, and explainable AI.
Key research trends include:
- Developing game theory-based explanations for machine learning predictions
- Modeling sports outcomes using Markov processes
- Analyzing forecasting reliability through betting odds
- Integrating data mining with medical modeling
He has been involved in numerous research projects funded by ARRS and international bilateral agreements, addressing topics like imbalanced data analysis, AI explainability, and hypercomputing applications.
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