Lasse Engbo Christiansen
Building: 303B, 010
2800 Kgs. Lyngby
Lasse Engbo Christiansen's research is within time series analysis. This includes stochastic dynamical systems, grey-box modelling, prediction, and optimization. He is also interested in spatial simulation of disease and spatial clustering tests.
His main research interests are within statistical modelling of spread of disease and bacterial growth and evolution. This includes development and selection of antibiotic resistance. The aim is to find a better way to administer known antibiotics such that resistance is reduced. Furthermore, Lasse Engbo Christiansen models financial data and also has an interest in challenges related to Smart Cities.
Lasse Engbo Christiansen is associate professor in statistics and dynamic systems at department for Applied Mathematics and Computer Science. He became M.Sc.Eng. in 2001 with a thesis on nonlinear dynamics of a railway vehicle on a disturbed track. In 2005 he was awarded the PhD degree in applied statistics from DTU. Prior to his current position he was post.doc. in 2005-2006 at University of California, Davis, where this research focused on how foot-and-mouth disease spreads and how to control it.
Lasse Engbo Christiansen lectures primarily time series analysis and applied statistics.
Lasse Engbo Christiansen is the program coordinator of the master of science program in Mathematical Modelling and Computation (MMC).
|1996 - 2001||MSc. Eng. - DTU|
MSc. Eng., PhD
|2008 -||Associate professor (DTU Informatics) - Technical University of Denmark, Department of Informatics and Mathematical Modelling|
|2006 - 2007||Post doc. (IMM) - Technical University of Denmark, Informatics and Mathematical Modelling|
|2005 - 2006||Post doc. (CADMS) - University of California, Davis, Veterinary Medicin, Centre for Animal Disease Modeling and Surveillance|
|2004 - 2005||Post doc. (IMM) - Technical University of Denmark, Informatics and Mathematical Modelling|
|2001 - 2005||PhD-student (IMM) - Technical University of Denmark, Informatics and Mathematical Modelling|
A Robust Statistical Model to Predict the Future Value of the Milk Production of Dairy Cows Using Herd Recording Data
Publication: Research - peer-review › Journal article – Annual report year: 2017
Models to Estimate Lactation Curves of Milk Yield and Somatic Cell Count in Dairy Cows at the Herd Level for the Use in Simulations and Predictive Models
Publication: Research - peer-review › Journal article – Annual report year: 2016
Publication: Research - peer-review › Poster – Annual report year: 2016
Public Library of Science, United States
BFI (2017): BFI-level 1, Scopus rating (2015): SJR 1.395 SNIP 1.044, ISI indexed (2013): ISI indexed yes
Indexed in DOAJ
Additional searchable ISSN (Electronic): 2297-1769
Frontiers Media, Switzerland
Indexed in DOAJ
Additional searchable ISSN (Electronic): 1873-1716
Elsevier BV, Netherlands
BFI (2017): BFI-level 2, Scopus rating (2015): SJR 1.265 SNIP 1.157, ISI indexed (2013): ISI indexed yes
Activity: Talk or presentation › Lecture and oral contribution
Publication: Commissioned - peer-review › Report chapter – Annual report year: 2016
Publication: Commissioned › Report – Annual report year: 2016