Rate My Professor Soojin Roh

Roh earned her Ph.D. from Texas A&M University in 2014, with a dissertation entitled 'Robust Ensemble Kalman Filter and Localization for Multiple State Variables' in the Department of Statistics. Her career includes presentations at statistical meetings, such as the 2014 Joint Statistical Meetings on localization methods for multivariate ensemble Kalman filters. Key publications feature 'Multivariate localization methods for ensemble Kalman filtering,' co-authored with Mikyoung Jun, Istvan Szunyogh, and Marc G. Genton, published in Nonlinear Processes in Geophysics in 2015 (Volume 22, No. 6, pp. 723-735). This paper proposes two strategies for localization functions applicable to multiple state variables at the same locations, evaluated via simulated observations in the bivariate Lorenz 95 model. Another significant paper, 'Observation quality control with a robust ensemble Kalman filter,' co-authored with Marc G. Genton, Mikyoung Jun, Istvan Szunyogh, and Ibrahim Hoteit, appeared in Monthly Weather Review in 2013 (Volume 141, No. 12, pp. 4414-4428).

At Monash University, Dr. Roh teaches statistics units, including coordinating SCI1020: Introduction to Statistical Reasoning in flexible mode for both semesters at Clayton campus. She served as Chief Investigator for the project 'Investigating the Effectiveness of H5P Interactive Content in Teaching a Second Year Statistics Unit (STA2216)' from December 2022 to December 2023. In a personal reflection, Roh notes her childhood love for mathematics led her to statistics, driven by curiosity about data origins and analysis pitfalls. She values statistics for revealing unexpected patterns in areas like climate research and medical studies on disease outbreaks such as COVID-19, enhancing societal benefits through data utilization.