Personal Information

Organization / Workplace

Durham, North Carolina United States

Industry

Education

Website

www.samsi.info
About

The Statistical and Applied Mathematical Sciences Institute (SAMSI), was established in 2002. SAMSI is a partnership of Duke University, North Carolina State University (NCSU), and the University of North Carolina at Chapel Hill (UNC). SAMSI is part of the Mathematical Sciences Institutes program of the Division of Mathematical Sciences at the National Science Foundation. SAMSI is housed in the Research Triangle Park, North Carolina.
Mission
SAMSI’s mission is to forge a synthesis of the statistical sciences and the applied mathematical sciences with disciplinary science to confront the very hardest and most important data- and model-driven scientific challenges.

Tags

samsi
clim
qmc
mums
transition
pmed
undergraduate workshop
machine learning
climate
precision medicine
bayesian
operator splitting
remote sensing
program on quasi-monte carlo and high-dimensional
gdrr
program on mathematical and statistical methods fo
trends and advances in monte carlo sampling algori
causal inference
statistics
frequentist
modeling
fiducial
extremes
personalized medicine
imsm
deep learning
blockchain
analytics
r software
ralph smith
clim fall 2017 course
statistics for climate research
modern math workshop
jim berger
marie davidian
nccu
richard smith
cryptocurrency
uncertainty quantification
model uncertainty
algorithm
climate change
bitcoin
finance
uncertainty
optimization
dimension reduction
david banks
multivariate
air quality
data assimilation
big data
healthcare
physicians
john nardini
data science
gerrymandering
redistriciting
quantitative
postdoc seminar
agent-based modeling
inverse problems
criminal justice system
data
stochastic
neural networks
elvan ceyhan
bo li
brian reich
quasi-monte carlo
murali haran
did
adversarial risk analysis
game theory
subspaces
system simulators
transportation
bayesian analysis
eric laber
clinical trials
communication
geophysical hazards
patient preference
sudipta dasmohapatra
professional development
uncertainty propogation
ernest fokoue
materials
mengyang gu
calibration
model discrepancy
emulators
bart
hierarchical model
spatial
probability
sea ice
estimation
nonsmooth
yawen guan
ansu chatterjee
sampling
maggie johnson
hurricanes
veronica berrocal
fred hickernell
art owen
ilse ipsen
amy braverman
mathematics
michael wehner
difference-in-difference
deep neural network
pcaa
artificial intelligence
michael kosorok
tumor heterogeneity
hyunjung lee
model selection
contingency table
entropy
decision analysis
sequential multiple assignment randomized trials
smarts
coastal resiliency
equilibrium
laura schultz
dynamic text
social networking
networking
model calibration
surrogates
dynamic treatment
single treatment decision regimes
jobs
hands-on problem set
erica rutter
heterogenity
reinforcement learning
mathematical surrogate
computer science
sacnas
bayesian inference
computation
bruce pitman
volcano
computer models
statistical models
matthew plumlee
engineering
elaine spiller
predictive models
ed george
michael wallace
yingqi zhao
type-ii diabetes
high-dimensional covariates
patient care
risk assessment
peter mucha
hiv
rho
savvysherpa
rheumatoid arthritis
light
epa
surya tokdar
forest
lidar
model
semiparametric
brook russell
gulf coast
networks
raphael huser
ken kunkel
climate extremes
risk
attribution
alexander gilbert
lattice
representative points
forensic science
decomposition
non-parametric regression
convex functions
amit apte
erik van vleck
zhengyuan zhu
bruno sanso
jessica matthews
emily kang
statistical emulation
spatial dependence
dorit hammerling
spatial statistics
data analysis
data systems
power systems analysis
generative models
kernels
molecular dynamics
whitney huang
extreme value analysis
spatial data
douglas nychka
data fusion
fall 2017 course
samsi professional development
probabilistic numerical methods
simon mak
peter kritzer
florian puchhammer
bayesian computation
high dimensions
lester mackey
roya amjadi
summer program on transportation statistics
pierre l’ecuyer
analysis
health
sea-ice
ice sheet
remote sensing data
climate modeling
precipitation
global
alexander d'amourr
sensitivity analysis
latent variable models
frederick eberhardt
zebrafish
human connectome project
meg
eeg
fmri
neuroimaging
jean barbier
high-dimensional inference
jennifer starling
women's healthcare
bcf
bayesian causal forests
bayesian additive regression trees
peng ding
pischke
angrist
lagged-dependent-variable
colin fogarty
observational studies
weak nulls
laura hatfield
medicaid
lu wang
t-rl
tree-based reiforced learning
acwl
adaptive contrast weighted learning
dtr
dynamic treatment regime
corwin zigler
coal-fired power plants
laine thomas
myomectomy
hysterectomy
diabetes
luke keele
bracketing
differences-in-differences methods
beth ann griffin
gun policy
stefan wager
supply-demand
mark van der laan
tmle
targeted minimum loss estimation
jared murray
model parameterization
mark borsuk
geoengineering
geopolitics
special guest lecture
alan karr
academic writing
hong wan
srikanth krishnamurthy
model life-cycle management
qutrack
matthew dixon
chainlet
transaction aware agents
anayltics
danny yuxing huang
decryption key
human trafficking
crime
libra
alexander lipton
digital trade coin
banking
tokens
fintech
peter adriaens
iot
tokenization
cyber-physical infrastructure system
infratech
nino antulov-fantulin
cunyet gurcan akcora
chainnet
sarit markovich
bitcoin cash
anita nikolich
phishing
cybersecurity
hacking
umar islambekov
ethereum
money
crypto-currency
martin mohlenkamp
canonical tensor
dimensionality
brian clipp
urban modeling
core3d
sattelite imagery
3d reconstruction
harsh parikh
optimization algorithm
flexible framework
malts
jinyuan jia
machine learning classifiers
deceptive mechanisms
adversarial machine learning
kelsey mcdonald
temporoparietal junction
video games
mri
bayesian nonparametric models
neural mechanisms
startegic games
social behavior
dorsomedial prefrontal cortex
dorsolateral prefrontal cortex
leighanne jarvis
random forest classifier
accelerometer-based classification system
peter hase
heirarchical prototypes
interpretable image recognition
sean ekins
deep neural nets
k-nearest neighbors
support vector regression
naive bayes
random forest
macrolactonedb
bioactive molecules
mark sendak
sepsis
xiaoyu cao
region-based classification
evasion attacks
xilong chen
beat-the-market trading startegy
hidden markov model
xinhao li
activity prediction
molecular properties
wayne thompson
machine learning algorithms
model fairness
feature extraction
feature engineering
data wrangling
david page
de-identified coded electronic health records
matthew phillips
fhir objects
mimic-iii
electronic health records
biomedical imaging
nilay tanik argon
healthcare operations
data-driven decision making
sayan mukherjee
3d sub-image analysis
geometric morphometrics
3d imaging
susan xia
stacking audience models
xipeng shen
deep neural networks
guassian process
ockhams prinicple of parsimony
cynthia rudin
cart
optimal scoring system
decision tree
poh-ling loh
linear networks
quoc tran-dinh
nonconvex optimization
stochastic composite
proxsarah algorithms
junier oliva
image applications
johannes schmidt-hieber
statistical method
relu networks
xiaoming huo
difference-of-convex
generalized linear models
optimal approximation
gan
amitabh basu
decision theory
james-stein estimator
estimators
anindya bhadra
deep models
complex models
horsehoe regularization
random initialization
em trajectory
em mapping
em algorithm
gaussian mixtures
rebecca willett
nuemann network
imaging
bianca dumitrascu
probablistic canonical correlation analysis
genomics medical pathology
jun zhuang
homeland security
national security
kaggle
gradient boosting trees
jesus rios
ara
joe halpern
cheap talk
nick polson
asset based modeling
deep reinforcement learning
vicky biers
game theoretic models
george michailidis
interbank lending transactions
publicly traded bank returns
correlation networks
network connectivity systemic risk
evans gouno
missing data
inverse bayesian formula
common-cause failure
alicia carriquiry
witness
juror
jury
court
crime scene investigation
lockhart prinicple
weidong tian
dynamic asset allocation
dynamic hedging
financial risks
dynamic financial decisions
nalini ravishanker
health analytics
high-frequency financial time series
tahir ekin
fraud analytics
gordon milbourn iii
critical societal system
fraud
jennifer clarke
risk analysis
amr
antimicrobial resistance
eunshin byon
stochastic computer models
reliability assessment
variance reduction
daniel eisenberg
cps
cyber physical social systems
resilience analytics
patricia hu
electric vehicles. james lambert
airport
maritime
public safety
braodband wireless networks
security
resilience
technology
human hazards
natural hazards
alyson wilson
laboratory for analytic sciences
simon wilson
spacecraft re-entry
probabilistic fault tree analysis
estimation models
power grid
pacific northwest national lab
glucose monitoring
hydrodynamic estimation
coastal imagery
usace
us army corps of engineers
winter storms
tropical storms
los alamos national lab
reward ignorant modeling
subpopulation heterogeneity
survival outcomes
joint longtitudinal outcomes
elizabeth slate
randomized reaction-diffusion model
tumor populations
nick henscheid
decision making
erica moodie
ai
composite outcomes
daniel luckett
virtual populations
eeg biomarkers
david carlson
brian williams
gradient-free construction
distributions
simon cotter
taylor asher
surge hazards
aaron danielson
gang li
fiducial computation
fiducial inference
storm surge
input distribution
estimating
eruption
kilauea volcano
computers
dimensional analysis
william welch
pzt
micro-air vehicles
biomorph actuators
nikolas bravo
deformation modeling
urban
bayesian optimization
vadim sokolov
evan baker
stochastic simulators
variable selection priors
marina vannucci
large-scale data
probability forecasts
vladimir vovk
multidimensional monotonicity
mbart
probabilistic principal component analysis
statistical sparsity
iducial
peter mccullagh
multiscale analysis
veronika rockova
monotone regression
credible intervals
subhashis ghosal
rui paulo
phillip dawid
simulator
discrepancy function
pierre barbillon
variable selection
jingshen wang
treatment effects
john snyder
gonzalo garcia-donato
david bickel
model revision uncertainty
idempotent probability
jan hannig
likelihood ratios
unconditional
conditional
average value
inference
nonsmooth functions
q-learning
hospital
patient vital signs
christopher mccann
medicine
glen wright-colopy
telba irony
positive controls
measurement error
rosa gini
mechanical ventilation
medical device analytics
brian walsh
evidence
hepatitis c
antivirals
richard zink
jason burke
practice-based
evidence-based
ilya lipkovich
subgroup identification
taylor ashley
flooding
tori tomiczek
gustavo cordoba
hazard assessment
madalina fiterau
vital sign
herb weisberg
harvest
jeff painter
crowdsourcing
rachael disantostefano
warren kibbe
precision oncology
stan young
meta-analysis
john schuler
price vectors
nonparametric estimation
simulators
agent-based transportation
politics
careers
data science careers
hazard forecasting
pierre gremaud
global sensitivity analysis
sir model
parameter selection
decision treatment regimes
multiple decision treatment regimes
mansoor haider
interviewing skills
resume
cv
parameter subspace analysis
xinyi li
cellular homegeneity
spatiotemporal data
classification in disease data
communities
lili wu
statistic emulators
gaussian processes
annie raymond
graph profiles
symmetry
veronica ciocanel
mathematical biosciences institute
intracellular transport
cytoskeleton roads
jo nelson
contact geometry
reeb dynamics
invariants
modern data science
henry segerman
icerm
pablo suárez-serrato
tina eliassi-rad
leo torres
network data
soledad villar
vote
geographic constraints
dustin mixon
geographic
partisan
jennifer bremer
north carolina legislature
lisa lebovici
markov chain monte carlo algorithm
maryland
democrat
approximation
hazard threat
robert wolpert
case study
uq data fusion
adaptive splines
atmoshperic dispersion model
laura swiler
surya kalidindi
knowledge systems
manufacturing
kevin carlberg
low-fidelity models
epistemic uncertainty
michael demkowicz
jenný brynjarsdóttir
dave higdon
model-based predictions
michael frenklach
b2bdc
bound-to-bound data collaboration
computer model calibration
georgios karagiannis
discontinuity
imperfect mathematical models
panel
nathan kutz
biology
physics
parametric dependencies
akil narayan
peter challenor
isaac newton
reduced-order models
tinsley oden
computational science
heterogenous
bani mallick
merlise clyde
nonparametric modeling
leonard smith
structural model error
dorothy wallace
immune systems
radiation
tumors
precision medi
charles manski
ecological inference
ruy ribeiro
africa
ebola
variability
yang kuang
hepatitis b
sirisha mushti
oncology
shiowjen lee
fda
cber
david margolis
lincoln labs
mit
thermomechanical
computational
film
sandia
grant weller
mit lincoln labs
john peach
reflection
elizabeth mannshardt
semiparametric models
covariate
andrew finley samsi
alaska
doug nychka
chris jones
mathematical
vegetation
arctic
ocean temperature
rainfall
yujing jiang
spatial precipitation
high-dimensional extremes
quantification
charlotte haley
doppler
wind speed
extreme value
hurricane harvey
david nunez torres
extreme value theory
hurricane maria
hurricane irma
caribbean
max-stable processes
extreme percipitation
spatial extremes
fei lu
model errors
stochastic parametrization
asim dey
insurance claims
jesse bell
human health
human mortality
temperature change
brian blanton
coastal hazards
rob erhardt
adaptive capacity
climate data
donata giglio
salinity
argo temperature
southern ocean
oxygen
adam monahan
air-sea fluxes
stochastic parameterization
environmental health
sohini raha
heatwaves
michael stein
oceanography
ben timmermans
parameter optimization
model error
unstable subspace
adway mitra
food systems
forward models
ice dynamics
jon hobbs
nathan lenssen
detection
tunable testbed
optimization methods
kaitlyn hill
food networks
christian sampson
sattelite
jon cockayne
conjugate gradient method
eigenvalue
dimensional integration
multivariate decomposition
oksana chkrebtii
adaptive grid design
discretization uncertainty
probability models
quasi-monte carlo simulations
monte carlo
tim sullivan
christopher oates
han lie
deterministic differential equations
porbabilistic integrators
mac hyman
statistical analysis
density estimation
overview
lucas mentch
mikael kuusela
latent noise
farid benmouffok
hilbert sums
composite problems
jean-christophe pesquet
marcelo pereyra
probability spaces
kazufumi ito
heinz bauschke
problems
massimiliano pontil
statististical guarantees
learning-to-learn
aditya mishra
compositional data
inverse covariance matrix
gersende fort
proximal-gradient algorithms
khai nguyen
nonlinear pdes
minh bui
differential equation
lilian glaudin
memoryless algorithms
multistep algorithms
jonathan eckstein
projective splitting
lorena bociu
boundary fluid-structure
zev woodstock
composite infimal convolutions
saverio salzo
forward-backward splitting algorithm
hamid krim
geometric regularization
irina gaynanova
multi-view data
yiyuan she
group-sparsity pursuit
robustness
thresholdings
silvia villa
inertial algorithms
noah simon
isao yamada
proximal splitting operators
heirarchical convex optimization
terry rockafellar
elicitable convexity
progressive decoupling
radu loan bot
nonconvex admm algorithm
boundedness
iterates
charles dossal
inertial methods
azam asl
bfgs
aleksandr aravkin
nonconvex
monte carlo techniques
earth science
nicolas fraiman
coupling
tutorial
chaos
predictability
cheng cheng
anton martinsson
distributed data systems
vineet yadav
gas fluxes
atmospheric inverse modeling
covariance matrices
computational process
george djorgovski
venkat chandrasekaran
computational and statistical
hui su
satellite data
climate model simulations
potential applications to distributed data
blocking methods
foundations
discussion
welcome
rajarshi guhaniyogi
distributed kriging
large scale kriging
jay morris
satellites
optimization methods in remote sensing
mike little
nasa
distributed access and analysis
matthias katzfuss
big spatial data
physical forward models
theory of data systems
jonathan hobbs
highresolution satellite data
carbon dioxide
atmospheric
ncar
high performance computing
manlio de domenico
multilayer modeling
dan crichton
software architecture
luca cinquini
distributed data analytics
earth system grid federation
environmental epidemiological
environmental exposure
monte carlo sampling algorithms
succeeding as a postdoc
snakes and ladders
aki nishimura
sampling discrete parameters
discontinuous hamiltonian monte carlo
shiwei lan
infinite-dimensional geometric mcmc
tamara broderick
data summarization
automated scalable bayesian inference
paris perdikaris
monte carlo sampling
multi-fidelity information fusion
matthew dunlop
hierarchical priors
non-guassian
mcmc sampling
youssef marzouk
sequential inference
low-dimensional couplings
stefan steinberger
jittered sampling
scott schmidler
paralell markov chain monte carlo
zhiqiang tan
adjusted mixture sampling
histogram analysis
antonietta mira
large-scale network data
approximate bayesian computation
questions
answers
qiang liu
stein variational approach
deep probabilistic modeling
sample quality
eric vanden-eijinden
infinite-swap
multiscale implementation
yian ma
correlated data
mcmc
hoang tran
high-dimensional functions
sparse polynomial
lawrence carin
variable learning
spacial extremes
climate data sets
development
reconstruction
paleo-climate
eva
climate research
large data
geostats
applications in climate context
spatial data analysis
jared rennie
scott stevens
dirty data
ncei
huang huang
models
nonstationary covariance modeling
kerry emanuel
storm
public lecture
estimating curves and surfaces
detection & attribution in climate science
analysis for climate model data
climate informatics
tom witelski
web pages
preparing cv's
christoph schwab
forward uq
inverse uq
multilevel qmc
recurring patterns
highway crashes
guannan zhang
high-dimensional partial integral differential equ
big-data
small-data
support points
qmc opening workshop
ian h. sloan
random fields
mike giles
empirical datasets
hermite spaces
numerical integration
sequences
point sets
dirk nuyens
higher-order convergence
roshan vengazhiyil
deterministic sampling
mahadevan ganesh
wave propagation model
heterogeneous media
mathieu gerber
sequential quasi-monte carlo
henryk wozniakowski
function values
linear tensor products
quasi-polynomial tractability
g. w. wasilkowski
variate integration
dongbin xiu
sequential function approximation
james hyman
high accuracy algorithms for interpolating and int
stein's method
sample
jose blanchet
operations research
optimal transport
algorithms
chris oates
numerical methods
bayesian probabilistic
jason west
human
patterns
crash
highway
lattice rules
error analysis
quasi-monte carlo methods
frances kuo
survey
random coefficients
pde
clémentine prieur
working group
applied mathematics
krisitie ebi
lagrangian model
alberto carrassi
epidemiologis research
environmental
howard chang
charles jackson
sea level
andrew gettelman
earth system
cloud
chris bretherton
turbulence
clouds
stochastic parameterizations
michal branicki
data assimilation techniques
multi-model predictions
multivariate extremes
montse fuentes
adverse birth outcomes
pollutants
multivariate dynamic spatial factor model
prabhat
extreme weather detection
imme ebert-uphoff
climate science
causality analysis
antarctic
statistical challenges
noel cressie
distributed data
daniel crichton
software
mathematical challenges
kenneth kunkel
big data in climate: opportunities and challenges
vipin kumar

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## Presentations

(429)## Documents

(8)Personal Information

Organization / Workplace

Durham, North Carolina United States

Industry

Education

Website

www.samsi.info
About

The Statistical and Applied Mathematical Sciences Institute (SAMSI), was established in 2002. SAMSI is a partnership of Duke University, North Carolina State University (NCSU), and the University of North Carolina at Chapel Hill (UNC). SAMSI is part of the Mathematical Sciences Institutes program of the Division of Mathematical Sciences at the National Science Foundation. SAMSI is housed in the Research Triangle Park, North Carolina.
Mission
SAMSI’s mission is to forge a synthesis of the statistical sciences and the applied mathematical sciences with disciplinary science to confront the very hardest and most important data- and model-driven scientific challenges.

Tags

samsi
clim
qmc
mums
transition
pmed
undergraduate workshop
machine learning
climate
precision medicine
bayesian
operator splitting
remote sensing
program on quasi-monte carlo and high-dimensional
gdrr
program on mathematical and statistical methods fo
trends and advances in monte carlo sampling algori
causal inference
statistics
frequentist
modeling
fiducial
extremes
personalized medicine
imsm
deep learning
blockchain
analytics
r software
ralph smith
clim fall 2017 course
statistics for climate research
modern math workshop
jim berger
marie davidian
nccu
richard smith
cryptocurrency
uncertainty quantification
model uncertainty
algorithm
climate change
bitcoin
finance
uncertainty
optimization
dimension reduction
david banks
multivariate
air quality
data assimilation
big data
healthcare
physicians
john nardini
data science
gerrymandering
redistriciting
quantitative
postdoc seminar
agent-based modeling
inverse problems
criminal justice system
data
stochastic
neural networks
elvan ceyhan
bo li
brian reich
quasi-monte carlo
murali haran
did
adversarial risk analysis
game theory
subspaces
system simulators
transportation
bayesian analysis
eric laber
clinical trials
communication
geophysical hazards
patient preference
sudipta dasmohapatra
professional development
uncertainty propogation
ernest fokoue
materials
mengyang gu
calibration
model discrepancy
emulators
bart
hierarchical model
spatial
probability
sea ice
estimation
nonsmooth
yawen guan
ansu chatterjee
sampling
maggie johnson
hurricanes
veronica berrocal
fred hickernell
art owen
ilse ipsen
amy braverman
mathematics
michael wehner
difference-in-difference
deep neural network
pcaa
artificial intelligence
michael kosorok
tumor heterogeneity
hyunjung lee
model selection
contingency table
entropy
decision analysis
sequential multiple assignment randomized trials
smarts
coastal resiliency
equilibrium
laura schultz
dynamic text
social networking
networking
model calibration
surrogates
dynamic treatment
single treatment decision regimes
jobs
hands-on problem set
erica rutter
heterogenity
reinforcement learning
mathematical surrogate
computer science
sacnas
bayesian inference
computation
bruce pitman
volcano
computer models
statistical models
matthew plumlee
engineering
elaine spiller
predictive models
ed george
michael wallace
yingqi zhao
type-ii diabetes
high-dimensional covariates
patient care
risk assessment
peter mucha
hiv
rho
savvysherpa
rheumatoid arthritis
light
epa
surya tokdar
forest
lidar
model
semiparametric
brook russell
gulf coast
networks
raphael huser
ken kunkel
climate extremes
risk
attribution
alexander gilbert
lattice
representative points
forensic science
decomposition
non-parametric regression
convex functions
amit apte
erik van vleck
zhengyuan zhu
bruno sanso
jessica matthews
emily kang
statistical emulation
spatial dependence
dorit hammerling
spatial statistics
data analysis
data systems
power systems analysis
generative models
kernels
molecular dynamics
whitney huang
extreme value analysis
spatial data
douglas nychka
data fusion
fall 2017 course
samsi professional development
probabilistic numerical methods
simon mak
peter kritzer
florian puchhammer
bayesian computation
high dimensions
lester mackey
roya amjadi
summer program on transportation statistics
pierre l’ecuyer
analysis
health
sea-ice
ice sheet
remote sensing data
climate modeling
precipitation
global
alexander d'amourr
sensitivity analysis
latent variable models
frederick eberhardt
zebrafish
human connectome project
meg
eeg
fmri
neuroimaging
jean barbier
high-dimensional inference
jennifer starling
women's healthcare
bcf
bayesian causal forests
bayesian additive regression trees
peng ding
pischke
angrist
lagged-dependent-variable
colin fogarty
observational studies
weak nulls
laura hatfield
medicaid
lu wang
t-rl
tree-based reiforced learning
acwl
adaptive contrast weighted learning
dtr
dynamic treatment regime
corwin zigler
coal-fired power plants
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myomectomy
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bracketing
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tmle
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stein variational approach
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qmc opening workshop
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dirk nuyens
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mahadevan ganesh
wave propagation model
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mathieu gerber
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stein's method
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jose blanchet
operations research
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chris oates
numerical methods
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highway
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survey
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working group
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noel cressie
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software
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big data in climate: opportunities and challenges
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