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Mathieu Kessler Neyer

  • Teaching area: Estadística e Investigación Operativa

Mathieu Kessler Neyer

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  • Teaching area: Estadística e Investigación Operativa
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About

Mathieu Kessler Neyer is Rector Magnífico

PhD in PhD in Mathematics, area: Mathematical Statistics from University Pierre et Marie Curie, Paris (FRANCE) - 1996
Master in Master Degree in Mathematics: Probability and Stochastic Processes. from University Pierre et Marie Curie, Paris (FRANCE) - 1993
Licensed in Graduate studies in Mathematics from University Paris Diderot (FRANCE) - 1992
Assessment of teaching: number of five-year periods assessed positively: 5
Assessment of research: number of six-year periods assessed positively: 4

Two lines of research can be identified in my production: on the one hand, I have studied statistical inference for stochastic processes, with emphasis on models driven by stochastic differential equations (SDE), Markov Chains and Hidden Markov Chains. I am in particular interested in theoretical results regarding the asymptotic behavior as well as in computational aspects related to the implementation of numerically efficient procedures. Moreover, I got increasingly interested in Bayesian statistics, with a focus on objective priors. Finally, in the last years, I have collaborated with Jesús Martínez Frutos, David Herreros and Francisco Periago at the a Universidad Politécnica de Cartagena, in the resolution of optimization problems in the presence of uncertainty.

A second and important line of research corresponds to my collaboration with colleagues from other areas. I began acting as a supporting statistician or data scientist at the University of Haute-Alsace Mulhouse in 1996. Being at a technical university in Cartagena has naturally provided a number of opportunities to serve as a statistician in applied problems, and I have been lucky enough to work intensively with friends in crystallography, electrical engineering (renewable energies) and animal production. I have been in charge of data munging and cleaning (doing that with R mainly) and statistical procedures, some of which quite challenging and interesting (e-g Reversible Jump MCMC algorithm for Bayesian Analysis of preferred crystallographic configurations, or a system of stochastic differential equations for the evolution of temperature in a house with AC)


Office Hours

Location
Day
Schedule
HOSPITAL de MARINA, Floor 0, Office B05
Wednesday
16:30 — 19:30
HOSPITAL de MARINA, Floor 0, Office B05
Thursday
16:30 — 19:30

Teaching

Course
Degree
Type
Duration
ECTS
INTRODUCTION TO DATA SCIENCE
Ir a Teams
Bachelor's degree in Telecommunication Systems
Type
O
Duration
2Q
ECTS
6
INTRODUCTION TO DATA SCIENCE
Ir a Teams
Bachelor's degree in Telematic Engineering
Type
O
Duration
2Q
ECTS
6

Abbreviation list

  • BS: Basic course
  • B: Required course
  • O: Elective course
  • A: Year-long
  • 1Q: 1st half
  • 2Q: 2st half

Teaching evaluation

Year
Course
Degree
Class
Survey respondent
Average (*)
2023-24
FUNDAMENTALS OF STATISTICAL INFERENCE
525102004
Bachelor's degree in Data Science and Engineering
Class
1
Survey respondent
14
Average
4.79
INTRODUCTION TO DATA SCIENCE
504104010
505104009
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
11
Average
5
2022-23
STATISTICS
504101007
505101007
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
4
Survey respondent
15
Average
4.8
INTRODUCTION TO DATA SCIENCE
504104010
505104009
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
13
Average
4.77
2021-22
STATISTICS
504101007
505101007
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
11
Average
4.91
INTRODUCTION TO DATA SCIENCE
504104010
505104009
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
2
Survey respondent
22
Average
4.91
STATISTICS English
504101007
505101007
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
8
Average
5
2020-21
STATISTICS
504101007
505101007
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
8
Average
5
INTRODUCTION TO DATA SCIENCE
504104010
505104009
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
27
Average
4.93
2019-20
INTRODUCTION TO DATA SCIENCE
504104010
505104009
Bachelor's degree in Telematic Engineering
Bachelor's degree in Telecommunication Systems
Class
1
Survey respondent
5
Average
5
(*) Average over a maximum of 5