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The group:
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Two postdocs:
Izabella Benczik (PhD 2003,
Eötvös)
Thierry
Platini (PhD 2008, Nancy)
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Four graduate students:
Jonathan
Cook (PhD ~2010)
Jiajia
Dong (PhD 2008)
Sayak
Mukherjee (PhD ~2009)
Abhishek Mukhopadhyay (PhD ~2010)
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Three undergraduate students:
Melvin
Amos (Physics)
John
Hoffman (Physics)
Sarah
Reeves (Physics)
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We always welcome visitors and exchange
students.
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From left, back row:
Max Lavrentovich, Jonathan Cook, Izabella Benczik, Sayak Mukherjee, Abhishek Mukhopadhyay, Melvin Amos, Nasrin Afzal.
Front row: Sarah Reeves, Royce Zia, Jiajia
Dong, Beate Schmittmann
Not in photo: John
Hoffman, Thierry Platini
Max, then an undergraduate at Kenyon College,
spent two summers with us (2007 and 2008). He is now a physics graduate
student at Harvard. Nasrin’s primary advisor
is our colleague, Michel Pleimling.
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 Funding:
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NSF, through DMR-0705152
This is our main bread-and-butter
grant. It pays for two to three postdocs, one graduate student, and the
undergraduates.
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NSF, through DGE-0504196
We are part of one of
Virginia Tech’s IGERT grants. The EIGER program pays for one
graduate student.
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NSF, through SBE-0244916
This
is Virginia Tech’s Advance grant. As Co-PI, Schmittmann has a small
travel budget for the group.
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Smaller amounts, mostly for travel, come from NATO.
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Links to recent NSF highlights:
DMR-0705152-08.ppt
DMR-0414122-07.ppt
DMR-0414122-06.ppt
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Current projects:
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Fundamental studies of non-equilibrium steady states
How
do we characterize a given non-equilibrium steady state (NESS)? What dynamical transition rates (in, e.g., a
master equation formulation) will give rise to the same, or a different, NESS? What information hides in the network
topology of (stationary) probability currents? In addition to these very
general questions, we study zero-range processes, asymmetric exclusion
processes, systems coupled to multiple temperature baths, and driven
diffusive systems.
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Computational modeling of protein production rates
How
does the inhomogeneity of the genetic code on an
mRNA molecule and the wide range of tRNA
abundances translate into the production rate of the associated protein?
We study models based on generalized asymmetric exclusion processes and
try to understand codon bias from a bioinformatics perspective.
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Complex networks and consensus formation in social
networks
Many
of the most exciting problems in science and engineering are
characterized by an underlying network structure. Examples include
critical infrastructures, communications, biological networks such as
cell regulatory networks or food webs, and social networks. We are
especially interested in adaptive (co-evolving) networks where the
dynamics of the nodes and the dynamics of the links feed back on one
another. For example, a friendship might weaken if one partner changes
his/her opinions. One interesting question, amongst others, concerns the
final state of the network: Does it fall into separate components? Will
all nodes settle into the same state?
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Spatio-temporal
dynamics of host-parasite interactions
If
a parasite’s long-term survival depends on the presence of the
host, how does the dynamics (spatial motion,
etc.) of the host affect the survival chances of the parasite? A simple example are cats and fleas: Fleas can survive
for some time away from the cat but eventually depend on a blood meal for
survival.
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