Curiosity. Rigor. Impact.
Hernando Ombao - Professor, STAT

Location

  • Building 1, Office 4126

Courses

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

Biostatistics. Statistical Signal Processing. Time Series Models. Functional Data Analysis. 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 Journal of the Royal Statistical Society - Series B. He is Co-Editor of the Handbook of Statistical Methods for Neuroimaging (CRC press, 2016) and Special Issue Co-Editor to the Journal of Time Series Analysis. Also, Professor Ombao is Panel Member of the Biostatistics Study Section at the US National Institutes of Health. 

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.

Why KAUST?

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

Euan, C., Sun, Y. and Ombao, H. (2019). Coherence-based time series clustering for brain connectivity visualization. Annals of Applied Statistics, 13, 990-115.
Schroeder, A. and Ombao, H. (2019). FreSpeD: Frequency-Specific Change-Point Detection Method in Multi-Channel Epileptic Seizure EEG Data. Journal of the American Statistical Association, 114: 115-128.
Ombao, H., Fiecas, M., Ting. C. M. and Low, Y. F. (2018). Statistical Models for Brain Signals with Properties that Evolve Across Trials. NeuroImage, 180(Pt B):609-618.
Cruz, M., Bender, M. and Ombao, H. (2017). Robust Interrupted Time Series Models for Analyzing Complex Healthcare Interventions. Statistics in Medicine, 20, 36(29), 4660-4676.
Fiecas, M. and Ombao, H. (2016). Modeling the Evolution of Dynamic Brain Processes During an Associative Learning Experiment. Journal of the American Statistical Association, 111, 1440-1453.
Ombao, H., Lindquist, M., Thompson, W. and Aston, J. (2016). Handbook of Statistical Methods for NeuroImaging. CRC Press. ISBN 9781482220971
Kang, H., Ombao, H., Linkletter, C., Long. N. and Badre, D. (2012). Spatio-Spectral Mixed Effects Model for Functional Magnetic Resonance Imaging Data. Journal of the American Statistical Association, 107, 568-577
Ombao, H., von Sachs, R. and Guo, W. (2005). SLEX Analysis of Multivariate Non-Stationary Time Series, Journal of the American Statistical Association, 100, 519-531.