Dr. Israel Martinez Hernandez

Lecturer/Assistant Professor in Statitics, Lancaster University, Mathematics and Statistics, UK

i.martinezhernandez@lancaster.ac.uk / GitHub / ORCID / LinkedIn / Google Scholar

👨‍🔬 Research Interest

• My primary research interests lie in developing novel statistical methodologies for analyzing:
  • large-scale and complex time series data, and
  • spatio-temporal data.
• I am highly motivated by real world problems such as data from Environment, Energy, Health, and Engineering.
  
• I am excited about functional data analysis (FDA) approach, which I find very promising and flexible in modeling this type of data. FDA assumes that data are in the form of continuous functions and can overcome several challenges faced in real applications. Some topics I am interested in include:
  • modeling,
  • exploratory data analysis,
  • hypothesis testing,
  • forecasting,
  • classification, and
  • efficient estimation.
• Part of my current project involves developing novel methodologies for healthcare technologies for 2050 @ QUEST. QUEST is a EPSRC funded project joint with colleagues at the University of Glasgow.
  

Employment

2023-present. Lecturer/Assistant Professor in Statitics, Lancaster University, Department of Mathematics Statistics.

2021-2022. Senior Research Associate, Lancaster University, Department of Mathematics Statistics. EPSRC funded “Quantum Imaging for Monitoring of Wellbeing Disease in Communities.” PI - Dr. Rebecca Killick

2018-2020. Post-Doctoral fellow, King Abdullah University of Science and Technology (KAUST). PI - Distinguished Professor Marc G. Genton

👨‍🎓 Education

• Jan 2014 - Dec 2017: Ph.D. in Probability and Statistics, Center for Research in Mathematics, CIMAT, Mexico.
• Aug 2011 - July 2013: M.S. in Probability and Statistics, Center for Research in Mathematics, CIMAT, Mexico.
• Aug 2006 - July 2011: B.S. in Mathematics, University of Benito Juarez, UABJO, Oaxaca, Mexico.

Career Achievements

• Member of National System of Researchers (SNI) in Mexico, Candidate level. 2020-2022.
• Second place, National contest of Junior Statistician. Mexican Statistical Association, 2014.
• Granted project (100,000 MXN): PADaJ Consulting (Performing Analysis for Decision-Making Judgment Consulting). Call for Entrepreneurship CIMAT-2015.

🗞️ Publications

Published

• Martínez-Hernández, I. and Killick, R. (2025). Changepoint Detection on Daily Home Activity Pattern: A Sliced Poisson Process Method. Biometrics.
• Martínez-Hernández, I. and Genton, M. G. (2024). Functional Time Series Analysis and Visualization Based on Records. Journal of Computational and Graphical Statistics.
• Martínez-Hernández, I. and Genton, M. G. (2023). Surface Time Series Models for Large Nonstationary Spatio-Temporal Datasets. Spatial Statistics. https://doi.org/10.1016/j.spasta.2022.100718.
• Baerenbold, O., Meis, M., Martínez-Hernández, I., Euán, C., S. Burr, W., Tremper, A., Fuller, G., Pirani, M., and Blangiardo, M. (2022b). A dependent Bayesian Dirichlet Process model for source apportionment of particle number size distribution. Environmetrics. https://doi.org/10.1002/env.2763.
• Martínez-Hernández, I., Gonzalo, J., and Gonzaléz-Farías, G. (2022a). Nonparametric Estimation of Functional Dynamic Factor Model. Journal of Nonparametric Statistics. https://doi.org/10.1080/10485252.2022.2080825. Rcode.
• Martínez-Hernández, I., and Genton, M. G. (2021). Nonparametric Trend Estimation in Functional Time Series with Application to Annual Mortality Rates. Biometrics. https://doi.org/10.1111/biom.13353. Rcode.
• Martínez-Hernández, I., and Genton, M. G. (2020). Recent Developments in Complex and Spatially Correlated Functional Data. Brazilian Journal of Probability and Statistics. http://dx.doi.org/10.1214/20-BJPS466
• Martínez-Hernández, I., Genton, M. G., and Gonzaléz-Farías, G. (2019). Robust depth-based estimation of the functional autoregressive model. Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2018.06.003

👨‍🏫 Teaching Experience

At Lancaster University, UK

• 2022: Lecturer of MATH453/553 Modelling Multilevel and Longitudinal Data.
• 2021: Supervisor of two MSc Dissertations, Lancaster University.
  • Analysing daily activity curves using functional data analysis and functional clustering.
  • Comparison of Univariate Time Series Analysis with Functional Time Series Analysis for Modeling Particulate Matter Concentrations (PM10).

At CIMAT, Mexico

• 2021: Lecturer of Time Series (Part II: Functional Time Series), Master in Computational Statistics, CIMAT, Mexico. For this module, I prepared lecture notes and workshop notes.

• 2013-2015. Teaching assistant, CIMAT, Mexico. MSc modules: Regression Models, Time series, Stochastic Models I, Stochastic Models II. My experience ranges through:

  • Marking assignments and projects
  • Preparing weekly revision sessions
  • Explaining the solution of selected problems.
  • Delivering R training courses