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Stefan Engblom
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- Position
- Professor in Scientific Computing
- Office Phone
- +46 18 471 27 54
- Fax
- +46 18 51 19 25
- Email
- stefan.engblom@it.uu.se
- Mailing Address
- Scientific Computing
Information Technology
Box 337
SE-751 05 Uppsala
Sweden
- Visiting Address
-
Polacksbacken Building 2
Room 2414a
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Find me at the Mathematics Genealogy Project...
...at the Research Gate...
...at Google Scholar...
...at ORCID....
...at ResearcherID....
...at arXiv...
...at GitHub.
I am...
...the Head of the Division of Systems and Control...
...the program coordinator for
the Master's
programme in Computational Science...
...the current faculty advisor
of UPPSALA SIAM
Chapter...
On the national side I am an elected member of
the Young Academy of
Sweden for the period 2016--2021. See
my presentation
web-page there.
Latest news and upcoming activities
2021
- January 26 (12.00--13.00): I will participate
in UPPTALK
on the topic CRUSH Covid - samverkan för att dämpa smittspridning i
Uppsala.
- January 29 Member of a grading committe at KTH.
- February 9--10 Academy meeting.
- March 25 Chairman of the Jury in
the Unga
forskare (Young researcher) competition.
- April 21--22 Academy meeting.
- May 29 Young academy's day!
Research
I am interested in most aspects of Scientific Computing, 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 Engineering
applications, and in Data-driven research.
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:
During spring 2021 I am looking for two PhD-students!
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.
Teaching
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).
Freeware
- 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.
Animations
- 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):
Miscellaneous:
Miscellaneous
I am involved in teaching Tango at Tangogruppen
Cambalache.
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