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Chris Volinsky, Director
Modeling graph and network data, graph matching; statistical
computation and visualization; data mining; Bayesian methodology;
Bayesian model averaging; baseball analysis (sabermetrics).
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Members of the Statistics Research Department
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Rick Becker
Visualization, statistical computing, graphics; co-inventor
of the S language.
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Suhrid Balakrishnan
Machine learning and knowledge discovery. Currently studying latent
variable models with application to collaborative filtering problems.
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Bob Bell
Statistical inference for data from complex samples, probabilistic
record linkage, machine learning methods, robust estimation.
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Simon Byers
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Sumit Chopra
Machine learning, pattern recognition, learning and inference algorithms
for large data sets.
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Tamraparni Dasu
Nonparametric methods that are robust and easily implementable on
large multivariate data; data streams; data quality: co-author
of Exploratory Data Mining and Data Quality.
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![[PHOTO]](pics/jimeng.jpg) |
Ji-Meng Loh Spatial statistics; bootstrap; anomaly detection.
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DeDe Paul
Consumer behavior modeling; data mining support for marketing; measuring
consumer word-of-mouth impacts.
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David Poole
Computer-intensive statistical procedures, capture-recapture
methods, analysis of call detail for traffic engineering purposes,
statistical use of simulation models, particularly population dynamics
models for marine mammals.
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Vaidyanathan (Ram) Ramaswami
Applied probability, algorithmic methods,
performance analysis and queueing theory, network monitoring algorithms,
internet performance.
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![[PHOTO]](pics/kshirley.jpg) |
Kenny Shirley
Bayesian modeling, multilevel models, hidden Markov models, and time series models
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Debby Swayne
Direct manipulation data visualization software and
methods; co-developer
of xgobi
and of the newer ggobi.
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Simon Urbanek
Statistical computing, data visualization, interactive analysis of
statistical forests
(KLIMT);
co-developer of
iPlots; member of the R
core development team.
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Allan Wilks
Statistical computing, computational geometry, graphics
languages, visualization, network data analysis; co-developer
of S.
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Visitors and Colleagues in Other Departments
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John Chambers
Statistical computing and languages; co-developer of S and
member of the R core development team; author of Programming with
Data: A Guide to the S Language.
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Richard Drechsler
Data visualization, scripting languages; co-creator of the
YOIX language.
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Colin Goodall
Signatures, models, visualization, and computational systems for
telecommunications usage/fraud and for health care outcomes:
real-time alerting and reporting. Statistical analysis of shape.
Data mining. Robust and exploratory data analysis
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Patrick Haffner
Machine learning, kernel machines, speech and language
understanding, OCR and document image processing and compression.
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Yifan Hu
Optimization, graph drawing and network analysis, sparse linear algebra and parallel computing.
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Walter Willinger
Statistical analysis and visualization of large sets of network
traffic data, probabilistic and statistical aspects of long-range
dependent processes and heavy-tailed distributions, with
applications to telecommunications and economics.
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Alumni with long and successful careers in our Lab
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Past visitors
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Past summer students
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| Milena Banjevic | Merrill Lynch |
| Zach Cox | Charles River Analytics |
| Alan Gous | Cariden Technologies |
| Carrie Grimes | Google |
| Giles Hooker | Cornell |
| Valerie Hyde | IBM |
| Rafal Kustra | University of Toronto |
| Dongyu Lin | The Wharton School, University of Pennsylvania |
| Tom Minka | Microsoft |
| Jen Neville | Purdue |
| Clayton Noll | Harvard |
| Susan Paddock | RAND |
| Steven Scott | Google |
| Eric Vance | Duke |
| Claudia Tebaldi | University of British Columbia |
| Casey Wolos | Harvard |
| Gina Maria Pomann | NC State |
| Anoushka Anand | U of Illinois |
| Piotr Mirowski | Bell Labs |
| Amitabha Ghosh | University of Southern California; Princeton University |
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