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Noel Cressie
ncressie@stat.osu.edu
My biostatistical research interests are principally in disease
mapping and its use in understanding the effect of regional-scale
environmental impacts on human health. This overlaps considerably
with the field of environmental epidemiology, and the mathematical
tools are being developed principally within the field of
spatial statistics. Another interest is in brain mapping using
fMRI data, where spatial statistical models prove to be very
useful in searching for areas of activation in the brain and
in the presence of considerable noise in the data.
Alexander Dynin
dynin@math.ohio-state.edu
My current research field is the mathematics of the Feynman
integral. There are intriguing applications of this integral
to biophysics. One topic is the entanglement and disentanglement
of a DNA molecule. The famous double helix consists of two
long strands of four bases: A, T, G, and C that are bonded
to their counterparts on the other strand. The strands may
be thought as polymers, i.e., long chains with randomly moving
joints. This connects with the theory of knots and links and
their topological invariants.
Kleinert's book "Path integrals in quantum
mechanics, statistics, and polymer physics", World Scientific,
1995.
Avner Friedman
afriedman@math.ohio-state.edu
My research areas are partial differential equations, control
theory, and stochastic differential equations. I am particularly
interested in nonlinear problems including free boundary problems.
My recent interests are applications of mathematics to models
in tumor growth, wound healing, and chemotaxis.
Jason Hsu
jch@stat.ohio-state.edu
I am working in the area of statistics called Multiple Comparisons,
where I develop statistical methodologies useful to the pharmaceutical
industry and the FDA. For example, one of my current projects
is to control for multiplicity in testing thousands of genes
simultaneously in microarray gene expression experiments.
Yuji Kodama
kodama@math.ohio-state.edu
My research areas are: Differential equations and their application
to mathematical physics, differential geometry, algebraic
geometry, and topology . My work includes integrable systems
(solitons, quasi-periodic solutions and perturbation methods,
normal form, multiple scales, averaging method, etc.).
Mario Lauria
lauria@cis.ohio-state.edu
My research interests cover different aspects of PC cluster
technology – architecture, system software, and applications.
On the applications side, I am studying how novel applications
pose new challenges to the designer of machines for high performance
computation. Particularly interesting to me is the use of
Computational Biology tools for data and compute intensive
tasks such as genome assemblies, genome analysis and phylogenetic
studies.
Stanley Lemeshow
lemeshow.1@osu.edu
My research areas are in statistical modeling and sampling
survey in medicine and epidemiology, such as estimating the
probability of mortality of critically ill patients, including
HIV/AIDS.
Shili Lin
shili@stat.ohio-state.edu
My research interests are in developing statistical and computational
methods for linkage and association studies of complex diseases,
for analysis of micro-array gene expression data, and more
generally, for modeling and analyses of biological processes.
I am particularly focused on the sort of data that render
conventional methods infeasible. One such example is data
from large families with complex relationships.
Yuan Lou
lou@math.ohio-state.edu
My current research interests are: applications of partial
differential equations to mathematical ecology; predator-prey,
competition of multiple species, and cross-diffusion model;
and migration and selection models in population genetics.
Steven Macechern
snm@stat.ohio-state.edu
My research interests in the biological sciences are in the
development and application of Bayesian methods. Of particular
interest are semiparametric and nonparametric Bayesian methods
for modeling data and the development of the computational
strategies required to fit the models. I am also working on
the development of alternative strategies, such as ranked
set sampling, for the collection and analysis of data.
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Haikady Nagaraja
hnn@stat.ohio-state.edu
I am interested in the statistical modeling of biological
data. In collaboration with a psychophysiologist and a cardiologist,
I am working on the problem of modeling of the heart period
data. Our work is providing new insights into the study of
respiratory sinus arrhythmia and the sympathetic and parasympathetic
nervous system. Another project, in collaboration with a neurologist,
involves the modeling of sleep duration data and a study of
its applications.
Kevin M. Passino
passino@ece.osu.edu
My research interests include mathematical modeling and analysis
of coordinated motion, social foraging, group choice, and
task allocation for multiagent (animal or vehicle) systems.
Methods include stability theory for distributed systems,
evolutionary game theory, and optimization. Applications include
honey bees, gray jays, multirobot systems, and multizone temperature
control.
Dennis Pearl
dkp@stat.ohio-state.edu
My research areas are: the probabilistic modeling of biological
phenomena and simulation-based estimation for high-dimensional
models; and collaborative research with biological scientists
including studies of the biological control of pests, laboratory
markers of cancer prognosis, the analysis of nucleotide sequence
data, and statistical phylogenetics.
Tom Santner
tjs@stat.ohio-state.edu
My research interests are in the design of experiments and
the analysis of discrete data. I am currently developing statistical
methods for designing computer experiments to find better
engineering designs of prosthetic devices and on a brain mapping
project using functional magnetic resonance imaging. I am
also interested in the efficient calculation of small sample
confidence intervals in a variety of biostatistical applications.
Srinivasan Parthasarathy
srini@cis.ohio-state.edu
My research interests are broadly in the areas of data
mining, machine learning and high performance computing especially
as they apply to biological and biomedical domains. Sample
projects currently underway include: protein structure analysis
and drug motif discovery; shape modeling and mining in the
context of eye disease detection; modeling and mining clinical
trials data for the study of hepatoxicity effects; graph mining
techniques in the context of protein protein interaction graphs;
and probablistic and deterministic learning models for rational
design problems such as protein crystallization trials.
Saleh Tanveer
tanveer@math.ohio-state.edu
My research areas in fluid dynamics include inviscid vortex
dynamics, turbulence, bubble dynamics, and Hele-Shaw flow,
and my research in crystal growth include directional solidification
and dendritic growth. The mathematical techniques I have been
using are partial differential equations in the complex plane,
and integro-differential equations.
David Terman
terman@math.ohio-state.edu
I am interested in the general areas of mathematical biology,
computational neuroscience, and dynamical systems. In particular,
I have developed and analyzed mathematical models for neuronal
systems including models for sleep rhythms and the Parkinsonian
tremor.
Joseph Verducci
jsv@stat.ohio-state.edu
I am interested in various applications of statistics to chemo-informatics.
One project involves searching large databases of chemicals,
first to organize compounds into groups of similar scaffold
structure, and then identify key substructures of pharmacophors
in the group that predicts specific types of biological activity.
Another project is to refine high throughput toxicity screening
methods based on chemical similarity to compounds tested in
animal studies, and then construct optimal designs for intensive
toxicity testing.
DeLiang Wang
dwang@cis.ohio-state.edu
My areas of expertise and interest include computational modeling
of auditory and visual functions, neural dynamics, and perceptual
computing.
Doug Wolfe
daw@mail.stat.ohio-state.edu
My current research revolves primarily around the development
of ranked set sampling techniques for a variety of problems.
Because the cost of many biological and medical measurements
can be substantial, this recently emerging methodology should
be of tremendous benefit to research studies in these areas.
I am very interested in exploring these possibilities in some
biological/medical applications.
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