Uppsala universitet 
Stefan Engblom
Short CV: (pdf)
Publications: (pdf)

Stefan Engblom

Stefan Engblom
Professor in Scientific Computing
Office Phone
+46 18 471 27 54 
+46 18 51 19 25 
Mailing Address
Scientific Computing
Information Technology
Box 337
SE-751 05 Uppsala
Visiting Address
The Ångström Laboratory, house 10
Room 106144
         Find me at the Mathematics Genealogy Project...
...at the Research Gate...
...at Google Scholar...
...at ORCID....
...at ResearcherID....
...at GitHub.

I am...
...the Director of eSSENCE...
...coordinating the TDB Seminar Series...
...the current faculty advisor of UPPSALA SIAM Chapter...
...a member of the board of Consor...

On the national side I was previously an elected member of the Young Academy of Sweden for the period 2016--2021. See my alumni presentation web-page there.

Swedish Young Academy

Latest news and upcoming activities



I am particularly interested in Scientific Computing in the intersection with Data-driven research and Data Science. I have extensive experiences in many aspects of Scientific Computing in general, in Numerical Modeling and -Analys in particular, as well as to some extent in High-Performance Computing. My main focus of applications are in the Biosciences at broad, but I've also taken an interest in traditional computational Engineering applications.

Current active research projects include Bayesian approaches for compute intensive data-driven models in epidemics, including in particular prediction, and multiscale modeling and parameterization of living cells, where spatial stochasticity is an important aspect of the modeling.

In case you are interested in doing a project work or a MSc-thesis, please feel invited to contact me for further discussions.

Read more (including publications and talks).

Open project proposals:

Computational Epidemics driven by Data
In this line of research we are interested in the trade-off between data on the one hand, and detailed modeling on the other hand. The application focus is in epidemics and concerns modeling under uncertainties and supporting risk-based decisions. Part of the work will be done in SimInf.
More details can be found here.

Computational cell population models: multiscale and multiphysics modeling
There are several openings for interesting projects within the software framework URDME. Suggestions include high-performance software development, advanced new modeling, and improving simulation efficiency and flexibility, as well as machine learning and data mining techniques.
More details can be found here.


Spring 2022: Numerical Functional Analysis (7.5hp, graduate course)
Spring 2022: Scientific Computing III 1TD397 (5.0hp).

Fall 2021: Scientific Computing III 1TD397 (5.0hp).
Spring 2020: Scientific Computing I 1TD393 (5.0hp).
Spring 2020: Numerical methods in stochastic modeling and simulations (7.5hp, graduate course).
Fall 2019: Scientific Computing II 1TD395 (5.0hp).
Previously also given 2018, 2017, 2016, 2015.
Spring 2019: Numerical Functional Analysis (7.5hp, graduate course)
Fall 2017:Advanced Numerical Methods 1TD050 (10.hp)
Fall 2016: Advanced Numerical Methods 1TD050 (10.hp)
Spring 2016: Numerical methods in stochastic modeling and simulations (7.5hp, graduate course).
Fall 2014: Numerical Functional Analysis (5.0hp, graduate course).
Spring 2014: Finite element methods II 1TD254 (5.0hp).
Fall 2012: Finite element methods 1TD253 (5.0hp).
Spring 2012: Classic Articles in Numerical Analysis (7.5hp, graduate course).
Fall 2010: Finite element methods 1TD253 (5.0hp).

Stefan Teaching Stefan Teaching


Please feel free to and use my software (Matlab/C/Mex) under a very liberal license. The software provided here includes a fairly wide range of subroutines useful in research, computations and for fun.

Please mail comments, suggestions, references, criticism. Please do not send support questions.

Download here.


If a picture tells more than a thousand words then a GIF-animation should tell at least a million...

SimInf and Data-driven epidemiological simulations:

URDME simulating stochastic spatial kinetics:
Surfactant in two-phase fluid flow (simulations by Minh Do-Quang):
Fibers in Stokes flow:
The master equation:
Autotuning (simulation by Marcus Holm):
Flow around airfoils (simulations by Paul Deglaire):


I am (sometimes!) involved in teaching Tango at Tangogruppen Cambalache.


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