Profiles

Prior to joining KAUST in 2019, Ortega Sánchez spent sixteen years working at the Mathematics Research Center (CIMAT) in Guanajuato, Mexico. He completed his postgraduate and graduate studies in London, where he studied mathematics at King’s College London before obtaining his Ph.D. in Probability Theory at Imperial College London. After his time in the U.K., Ortega Sánchez returned to his native Venezuela, where he worked for over 20 years at the Universidad Central de Venezuela and the Venezuelan Scientific Research Institute..

He has taught courses on stochastic models, time series, measure theory, advanced probability, extreme value theory, statistical consulting, functional data analysis, applied statistics, time series, and design of experiments. His career has seen him teach courses at several institutions worldwide, including the University of Paris-Sud, France, and the University of Valladolid, Spain.

Ortega’s primary role at KAUST is teaching statistics and providing additional mathematics support.

Throughout his career, Ortega’s research has focused on stochastic processes, specifically Gaussian processes and time series, with applications in oceanography and biostatistics. More recently, his work has focused on functional data analysis.

Hernando Ombao is a professor in the Statistics Program and the principal investigator of the Biostatistics Group at KAUST. His research focuses on developing time series models and novel data science methods for analyzing high-dimensional complex biological processes. He leads a group of researchers specializing in spectral and time-series analysis, functional data analysis, state-space models, and signal processing for brain signals and images. His group collaborates closely with neuroscientists to model the associations between neurophysiology, cognition and animal behavior.

Before joining KAUST, Professor Ombao was a tenured faculty member at the University of Illinois Urbana-Champaign, U.S., Brown University, U.S. and the University of California, Irvine, U.S. He earned a B.Sc. in Mathematics in 1989 from the University of the Philippines, an M.Sc. in Statistics in 1995 from the University of California, Irvine, and a Ph.D. in biostatistics in 1999 from the University of Michigan.

Ombao is an elected fellow of the American Statistical Association. He has been awarded several grants as a principal investigator by the U.S. National Science Foundation. In 2017, he received the UC Irvine School of Information Sciences Mid-Career Award for Research. He has served as a panel member of the Biostatistics Study Section at the U.S. National Institutes of Health and as an associate editor of leading statistical journals. He is co-editor of the book Handbook of Statistical Methods for Neuroimaging (CRC Press, 2016) and co-editor of a special issue of the Journal of Time Series Analysis.

At KAUST, he holds secondary appointments in the Applied Mathematics and Computational Sciences (AMCS) and the Bioengineering Programs. He also serves as chair of the Institutional Biosafety and Bioethics Committee. Ombao actively collaborates with researchers across the campus and is a co-founder of the interdisciplinary KAUST Neuro-AI Laboratory (NAIL).

Professor Ombao’s research focuses on the statistical modeling of time series data and the visualization of high-dimensional signals and images.

He has developed a coherent set of methods for modeling and inference on the dependence of complex brain signals: testing for differences in networks across patient groups, identifying biomarkers, classifying diseases based on networks and modeling associations between high-dimensional data from different domains, such as genetics, brain function and behavior.