Hi! I’m Mary Lai, a Filipino statistician based in Houston, Texas. I am a Postdoctoral Fellow at the Department of Mathematics, University of Houston. Prior to joining University of Houston in 2021, I was a Ph.D. student in the Spatio-Temporal Statistics group at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

Work and Research

I use spatio-temporal geostatistical methods to model and predict Gaussian spatio-temporal processes. These methods aim to understand the dependence in a Gaussian spatio-temporal process across space and time by seeking correlations and they are adequate for many real-life spatio-temporal phenomena. My Ph.D. dissertation was about constructing univariate and multivariate, stationary and nonstationary spatio-temporal covariance functions with emphasis on transport phenomenon. I applied my methods on a variety of environmental datasets such as wind speeds, temperature, precipitation, and particulate matter.

I also have expertise in high performance computing for spatio-temporal data applications. My previous works in this area include modeling and prediction on 500,000 space-time locations.

My research interest is on data-driven climate change modeling and forecasting and uncertainty quantification using geostatistical methods and deep learning models.

Educational Background

I received my BS and MS degrees in applied mathematics from Ateneo de Manila University, Philippines, in 2015 and 2016, respectively, and my Ph.D. in Statistics from the King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

Research Interests

My research interests include climate statistics, spatio-temporal statistics, extreme statistics, high-performance computing, big data, multivariate analysis, deep learning, machine learning, data science \& visualization, cascading disasters, risk management.