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Frantzeska Lavda is a dedicated doctoral assistant at the University of Geneva, specializing in statistical methods and data analysis. Her research interests encompass a broad range of topics in statistics, particularly focusing on Recurrent Neural Networks (RNNs) for time series analysis. Throughout her academic career, she has contributed significantly to various projects that involve forecasting and data-driven methodologies, aiming to enhance predictive accuracy in numerous applications. Lavda has been involved in teaching courses related to data mining and Bayesian statistics, facilitating learning and engagement among students. Her academic journey is marked by a strong emphasis on practical applications of statistical theories and innovative methodologies. In addition to her teaching responsibilities, Lavda is active in research, collaborating with fellow scholars and participating in academic events to further expand her expertise and knowledge in the field of statistics.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.