My aim is to uncover dynamic changes in brain networks where interactions between brain regions exhibit changes over time in order to provide fundamental insights into human behavior, cognition, and emotions.
Hernando Ombao - Professor, STAT


  • Building 1, Office 4126


Education Profile

  • PhD in Biostatistics, University of Michigan
  • MS in Statistics, University of California Davis
  • BS in Mathematics, University of the Philippines

Hernando Ombao is a Professor of Statistics and Principal Investigator of the KAUST Biostatistics Group. His main area of research is on developing statistical models and methods for analyzing high dimensional complex biological processes. At KAUST, he directs a group of researchers working on methods for brain signals and images using spectral analysis, time series analysis, functional data, state-space models and signal processing. His group actively collaborates with neuroscientists in modeling associations between neurophysiology, cognition and animal behavior.

Education and early career

Prior to joining KAUST, he was a tenured faculty at the University of Illinois Urbana-Champaign, Brown University and the University of California, Irvine. He obtained his BS degree in Mathematics from the University of the Philippines, an MS degree in Statistics at the University of California, Irvine and a Ph.D. degree in Biostatistics from the University of Michigan.

Areas of expertise and current scientific interests

Statistical Signal Processing, Time Series Analysis, Functional Data Analysis and Applications to Neuroscience and Biomedical Data.

Awards, Honors and Special Lectures

  • Mid-Career Dean’s Award for Research (2017) UC Irvine School of the Information and Computer Sciences
  • Elected Fellow, American Statistical Association (2016)
  • Grant on Studies on Signals and Images Via the Fourier Transform, NSF Division Mathematical Sciences, 2015-2018
  • Grant on Bayesian State-Space Models for Behavioral Time Series Data, NSF Division Social and Economic Sciences, 2014-2017
  • Grant on Localized Cross-Spectral Analysis and Pattern Recognition in Non-Stationary Signals, NSF Division of Mathematical Sciences, 2004-2008​

Career recognitions

Professor Ombao is an Elected Fellow of the American Statistical Association. He was also a Principal Investigator of several grants awarded by the US National Science Foundation. In 2017, he received the UC Irvine School of Information Sciences Mid-Career Award for Research.

Professional and editorial activities

Professor Ombao serves Associate Editor for the Journal of the American Statistical Association (since 2005). He also served as an Associate Editor for Metron; Journal of Statistical Analysis and Data Mining; and the Journal of the Royal Statistical Society. He is Co-Editor of the Handbook of Statistical Methods for Neuroimaging (CRC press, 2016). 

Why Biostatistics?

Biostatistics is a natural playground for data scientists who are fascinated by applications of mathematics, statistics, and computing to discovering new frontiers in medicine and in the understanding of the human mind.


KAUST brings together scientists who are at the cutting-edge of their respective areas. One can get energized by the passion and zeal of the researchers and students from all over the world.

Selected Publications

Euán, C., Ombao, H., & Ortega, J. (2018). Spectral synchronicity in brain signals. Statistics in Medicine, 37(19), 2855–2873. doi:10.1002/sim.7695
Euán, C., Ombao, H., & Ortega, J. (2018). The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure. Journal of Classification, 35(1), 71–99. doi:10.1007/s00357-018-9250-5
Pluta, D., Yu, Z., Shen, T., Chen, C., Xue, G., & Ombao, H. (2018). Statistical methods and challenges in connectome genetics. Statistics & Probability Letters, 136, 83–86. doi:10.1016/j.spl.2018.02.048