David Crevillén García

  • Contact
  • Teaching area: Estadística e Investigación Operativa
  • Stochastic analysis and modelling / Computational statistics / Applied statistics

David Crevillén García




  • EMAIL
  • Phone

  • Teaching area: Estadística e Investigación Operativa
  • Stochastic analysis and modelling / Computational statistics / Applied statistics
Internet Explorer no está soportado por esta aplicación

Recomendamos que instale un navegador más moderno como por ejemplo Mozilla Firefox, Microsoft Edge (Windows 10), Vivaldi, Brave, Opera o Google Chrome. Este sitio web también es compatible con Safari en macOS.

About

David Crevillén García

PhD en Matemática Aplicada y Estadística en la Universidad de Nottingham (REINO UNIDO) - 2016
Licensed en Matemáticas en la Universidad de Murcia (ESPAÑA) - 2002


I obtained my PhD in Applied Mathematics and Statistics from The University of Nottingham in 2015. During my thesis, I developed various statistical and computational techniques for performing uncertainty quantification in computationally expensive models of carbon capture and storage processes.

I have an established interest in the relationship between machine learning and mathematical models, in particular for those involving environmental fluid mechanics. My primary area of research has been the development of new techniques for uncertainty quantification in stochastic models, these include the use of linear (e.g., principal component analysis) and non-linear (e.g., manifold learning) dimension reduction methods defined in high-dimensional input and output spaces, and the development of statistical surrogates for computationally expensive numerical simulators, with particular focus on Gaussian process emulators. I have also investigated multilevel Monte Carlo and quasi-Monte Carlo methods for uncertainty quantification in flow and transport in random heterogeneous porous media.

In the past, I have worked as a postdoctoral researcher at the University of Warwick. Withing the Statistical Department, I was involved in the investigation of spatial arrangements of dysfunctional pixels in Computed Tomography by studying point patterns, complete spatial randomness, clustering and regularity.

I also worked during two years in a research centre called LUCIDEON, based on Stoke-on-Trent (UK), where as part of the Simulation and Modelling Department I was working on the numerical simulation of powder compaction and dead-end filtration processes by using computational modelling covering both Finite Element and fluid dynamic techniques.

My recent investigations have been focused on investigating the application of machine learning to the prediction of crowd and traffic motion in modern and future urban environments. More precisely, I worked on developing and applying appropriate machine learning and uncertainty quantification techniques to a) make city-scale simulation computationally realisable; b) use real-time data to improve predictive capability of crowd/traffic models and to quantify uncertainty in model outputs.

Office Hours

Añadir Tutoría
Location
Day
Schedule
HOSPITAL de MARINA, Floor 0, Office B033
Las tutorías deben concertarse de antemano con el profesor vía correo electrónico.
Monday
10:00 — 11:00
HOSPITAL de MARINA, Floor 0, Office B033
Las tutorías deben concertarse de antemano con el profesor vía correo electrónico.
Monday
13:00 — 14:00
HOSPITAL de MARINA, Floor 0, Office B033
Las tutorías deben concertarse de antemano con el profesor vía correo electrónico.
Tuesday
11:00 — 15:00
Tutorials will by carried out by request of the student sending a mail to david.crevillen@upct.es

Teaching

Course
Degree
Type
Duration
ECTS
APPLIED STATISTICS
Grado en Ingeniería Eléctrica
Type
BS
Duration
2Q
ECTS
6
APPLIED STATISTICS
Degree in Agri-food and Biological Systems Engineering
Type
B
Duration
1Q
ECTS
4.5
APPLIED STATISTICS
Degree in Civil Engineering
Type
BS
Duration
1Q
ECTS
6
APPLIED STATISTICS
Degree in Energy and Mineral Resource Engineering
Type
BS
Duration
1Q
ECTS
6

Abbreviation list

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

Publications

Year
Type
Title
2019
Journal ar

Screening of effective electrolyte additives for zinc-based redox flow battery systems

David P. Trudgeon / Kaipei Qiu / Xiaohong Li / Tapas Mallick / Oluwadamilola O. Taiwo / Barun Chakrabarti / Vladimir Yufit / Nigel P. Brandon / David Crevillen-Garcia / Akeel Shah

ISSN: 03787753

Journal of Power Sources