New paper on intrinsic connectivity network for fMRI data.
Meini Tang , Chee-Ming Ting , Hernando Ombao - BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data. [Link]
New paper “Shape-preserving prediction for functional time series” by Post-Doc Jiao accepted for publication at the Electronic Journal of Statistics.
Shuhao Jiao and Hernando Ombao: Shape-preserving prediction for functional time series. [Link]
New paper on exploring topological structures of the COVID-19 virus spike protein.
Moo K. Chung and Hernando Ombao: Topological Data Analysis of COVID-19 Virus Spike Proteins. [Link]
New paper on exploring dependence between signals through the oscillatory decompositions with toolbox.
Hernando Ombao and Marco Pinto: Spectral Dependence. [Link]
Check the spectral depence toolbox here.
New paper on Negative Binomial Processes accepted for publication in the Scandinavian Journal of Statistics. Lead author: Wagner Barreto-Souza.
Wagner Barreto‐Souza and Hernando Ombao: The Negative Binomial Process: A Tractable Model with Composite Likelihood-Based Inference. [Link]
New paper on local Granger causality for non-stationary time series with collaborators from Waseda University.
Yan Liu, Masanobu Taniguchi, Hernando Ombao: Statistical Inference for Local Granger Causality. [Link]
Professor Hernando Ombao to serve as a statistical adviser to the EU-funded AI-Mind Project based in Oslo University, Norway.
Project AI-Mind: Artificial Intelligence for Dementia Prevention. [Link]
New paper on semiparametric time series models (International Journal of Forecasting)
Gisele de Oliveira Maia, Wagner Barreto-Souza, Fernando de Souza Bastos, Hernando Ombao: Semiparametric time series models driven by latent factor. [Link]
New paper on dynamic structure in brain networks (IEEE Trans Med Imaging).
Chee-Ming Ting, S. Balqis Samdin, Meini Tang, Hernando Ombao: Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach. [Link]
New paper submission on extremal dependence for multi-channel EEG data.
Matheus B. Guerrero, Raphaël Huser, Hernando Ombao: Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data. [Link]
Ph.D. student Anass El Yaagoubi Bourakna and his team made it to the finals of the NEOM AI Challenge.
Anaas's team participated under the Mobility category of the challenge. Leveraging AI and Tramway transportation systems, they proposed to build the next generation of urban public transportation. Their goal was to suppress delays, increase reliability, shorten transportation times and improve safety by designing a fully autonomous transportation system that never stops in passengers' waiting-stations. [Read more]
Anaas's teammates were Norah Almasoud and Zohra Fatimah.
The Biostatistics Group has been working on COVID-19 forecastings.
- COVID-19 epidemic simulator: [Link]
Shuhao Jiao will join the KAUST Biostatistics Group as a Post-Doctoral Scholar effective October 2019. Dr. Jiao received his PhD University of California, Davis. His research is on functional time series.
Ombao to give a seminar at the University of Florence October 2019. [Link]
Students present research at the JSM 2019 (Denver):
Abdulrahman Althobaiti: Visualization and Analysis of Spectral Features in Time Series
Anass Bourakna: Stationary subspace representation of High dimensional time series
Guillermo Garcia: Bayesian nonparametric estimation of the spectral density function with application to rat LFP data
Matheus B. Guerrero: A New Perspective on Modeling Count Time Series Data
Meini Tang: State-related Dynamic Community Detection with Markov-switching Stochastic Block Model
Ombao presented research at the Universidade Federal de Minas Gerais, Brazil. [Link]
Ombao organized the workshop on Statistics in Neuroscience 2019 hosted at La Sapienza Rome and gave a department seminar. [Link]
Ombao presented research at ENAR 2019 (Philadelphia).
Guillermo Garcia, PhD Student, presented research at ENAR 2019 (Philadelphia): Spectral Analysis of Brain Signals: A New Bayesian Nonparametric Approach.