Talk - Scaling Laws in Random Hypergraph Models

Quantitative researcher with a PhD in Mathematics, combining expertise in stochastic modeling, statistical inference, and machine learning with industrial experience in developing predictive systems. Experienced in large-scale time-series analysis, uncertainty quantification, and rigorous model validation, with strong Python/C++ skills and a proven track record of translating research into production software. Currently developing intraday electricity-price models and stochastic-control methods for optimal liquidation at Aarhus University, in collaboration with an energy trading firm.