Dr Jafet Belmont Osuna
- Lecturer in Statistics and Data Analysis (Statistics)
Biography
Bsc. in Biology from the School of Sciences, UNAM, México in 2014 and Specialist in Applied Statistics from the Research institute in Applied mathematics (IIMAS, UNAM) in 2016. Then, received MSc in Environmental Statistics from the University of Glasgow in 2017 and PhD in Statistics in 2021. Employed by University of Glasgow since 2018.
Research interests
Research area
My research focuses on developing statistical models to analyse biodiversity data from citizen science projects and applying Bayesian methods to characterize biological communities in changing environments. I am also interested in developing and exploring machine-learning techniques to analyse complex ecological and environmental data.
Current Research
Currently, I investigate methods to estimate species distributions while accounting for the observational process of how data is collected across different citizen science biodiversity monitoring schemes in the UK. I am also interested in developing model validation and diagnostic tools for some commonly used ecological models. I am also part of a multidisciplinary team aiming to develop a generalised modelling framework to integrated species distribution models using INLA (integrated nested Laplace approximation). Such approach will provide both a generalized theoretical framework that can cover a wide range of scenarios and a single practical tool for statisticians and ecologists alike.
Research groups
- Statistics and Data Analytics Group
- Species distribution modelling using citizen science data
Research groups
Teaching
Lecturer:
- Data Mining & Machine Learning II (ODL)
- Data Analysis (STATS3011/STATS4052)
Involved in delivering teaching, tutorial sessions and developing material for the following courses:
- Probability level M (STATS5024)
- Statistical Inference level M (STATS5028)
- Regression Models level M (STATS5025)
- Data Mining & Machine Learning I (ODL)
- Predictive Modelling (ODL)
- Data Management and Analytics using SAS (ODL)
- Probability & Sampling Fundamentals (ODL)
-
Stochastic Processes (STATS4024/5026)
-
Flexible Regression (STATS4040/STATS5052)
-
Advanced Bayesian Methods (STATS4038/STATS5013)
Professional activities & recognition
Prizes, awards & distinctions
- 2016: Awarded to the postgraduate student with the highest GPA and who graduated with the highest honors and exceptional thesis defense. (Medalla Alfonso Caso)