The Statistics Department is located in 132 Baker Hall on the Carnegie Mellon campus.
You can reach us by phone at (412) 268-2717 and by fax at (412) 268-7828.
Our mailing address is
Department of Statistics
Professor Genovese's research focuses on complex and high-dimensional statistical
problems in the sciences, including neuroscience, evolutionary biology,
and cosmology. He enjoys
getting “in the trenches” of scientific applications.
He also works on theoretical questions related to inference
for functions and other infinite-dimensional objects, with a recent emphasis
on finding low-dimensional structures in data,
and he has a strong interest in computational methods and theory.
When he's not working at his computer or in meetings, he's been known to
escape into the wilderness.
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Don't mess with Texas! Professor Nugent's research focuses on finding
clusters (similar groups) in high-dimensional data and on analyzing text
(e.g., web pages, documents) and record (e.g., census) data.
She is an award-winning and innovative instructor.
Besides running the Undergraduate Statistics Program, Professor Nugent is also the
faculty advisor for the Economics and Statistics joint major.
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The doctor is in! Professor Seltman worked for fifteen years
as a clinical pathologist before becoming a statistician. His research focuses
on the modeling and analysis of psychiatric, medical, and genetic data and on building
methods to combine results across different studies. He is an outstanding
instructor and advisor who always goes the extra mile for his students.
Besides running the Undergraduate Statistics Program, Professor Seltman is the
faculty advisor for the core Statistics major.
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The go-to person for your questions!
As Academic Advisor, Ms. Nielsen is the point of contact for advising questions.
She knows the system inside and out, and she can help you find answers, solve
your problems, and connect you with an appropriate faculty advisor.
In addition to her advising role, she is also the Department's Academic Coordinator,
responsible for many aspects of our undergraduate program.
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Professor Tibshirani's research focuses on statistical inference for high-dimensional data.
This deals with the challenges of large, modern data sets where
each data point is a high-dimensional object,
such as an image or document (high-dimensional vector),
a curve (function in some infinite-dimensional class),
or a snapshot of a network (graph with potentially very many nodes and edges).
He has recently solved two significant open problems in this area.
His work lies at the boundary between Statistics and Machine Learning,
and he brings substantial experience to his role as advisor for this joint major.
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Professor Ventura's research focuses on statistical problems in cognitive neuroscience.
She often works with data that directly measures neuronal activity, and
she is interested in methods of “decoding” such spike-train data to reconstruct the
stimulus and understand the information that can be extracted about brain systems.
She has made several fundamental advances in this area, including work
on neural prosthetics.
Her experience in this area makes her ideally suited to serve as advisor
for this track.
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Professor Shalizi is widely known for his eclectic interests,
his popular blog,
and his legendary book reviews.
His research focuses on dynamical systems (and their statistical implications),
networks (social and otherwise), and fundamental statistical theory.
He applies his work to problems in a wide variety of areas,
including sociology, physics, and neuroscience.
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Anchoring our advising lineup is one of the early leaders in modernizing Statistics education.
Professor Greenhouse's research focuses on statistical problems in psychiatry and epidemiology,
clinical trials and meta-analysis, and the design and analysis observational studies.
He is an award-winning instructor and tireless advisor, and he
created our trend-setting introductory statistics sequence. In addition to his role as
Statistics Advisor, Professor Greenhouse also works with additional Statistics majors and
runs the Masters in Statistical Practice program in the Department.
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