Hello, I am a Data Scientist. My research focuses on addressing epistemic uncertainty that arises in data analysis and AI applications, primarily through Bayesian methods. My main research area is recommender systems. I became interested in this field after recognizing the conceptual parallels between my undergraduate training in Economics—particularly in modeling consumer preferences and choices—and personalized algorithms that infer user preferences and recommend relevant items.
I plan to extend my research in three directions: (1) developing personalized algorithms based on graph neural networks for applications such as bundle recommendation, group recommendation, and knowledge tracing; (2) developing time-series forecasting models that explicitly account for epistemic uncertainty, using methods such as nonparametric estimation and stochastic processes; and (3) exploring auction theory, particularly Bayesian approaches to auctions within a game-theoretic framework.