Snehalata Huzurbazar Named as Deputy Director of SAMSI

April 23, 2012

SSHuzurbazarnehalata Huzurbazar, Associate Professor of Statistics at the University of Wyoming, has accepted the position of Deputy Director of the Statistical and Applied Mathematical Sciences Institute (SAMSI) for the next two years. Huzurbazar will take a leave of absence from the University of Wyoming while she performs her duties at SAMSI, starting on July 9. She will also be a member of the research faculty at North Carolina State University in the Statistics Department. The announcement was made by Dr. Richard Smith, Director of SAMSI.

“We are very impressed with Snehalata’s background and think she will bring a fresh perspective to the development of SAMSI’s programs and will be instrumental in our education and outreach efforts,” remarked Smith.

In her new position, Huzurbazar will help administer SAMSI programs and will help develop future programs. She will also be involved with the education and outreach efforts and will work on staff and personnel issues. Huzurbazar will be a part of the directorate, which comprises the director, three part-time associate directors and the deputy director.

Huzurbazar received her B.A. degree from Grinnell College in 1984, her M.A. degree in Economics from Vanderbilt University in 1988, and her Ph.D. in Statistics from Colorado State University in 1992. She was an assistant professor at the University of Georgia from 1992-1995, and has been at the University of Wyoming since 1995. At UW, she has been an affiliate of the Science and Mathematics Teaching Center since 2003. She was also an adjunct professor of Women’s Studies from 2003-2008.

Huzurbazar spent some time at SAMSI last year as a visiting research fellow in the Analysis of Object Data program. One of the reasons she was attracted to the deputy director’s position was because SAMSI is the only National Science Foundation (NSF) institute that explicitly includes a focus on Statistics. She is particularly interested in encouraging young people to pursue careers in statistics and mathematical sciences. “Making an impact on outreach is really important to me. We often have trouble getting people into the mathematical sciences. I think we need to do a better job attracting students into mathematical sciences and inform them about various career options,” said Huzurbazar.

Much of Huzurbazar’s recent time has been spent building collaborations with colleagues in a variety of disciplines ranging from evolutionary bioinformatics to the geosciences, broadly defined. In evolutionary bioinformatics, she is working on the statistical issues surrounding the data generation pipelines. “Genomes for various species are sequenced. Then the data from the sequenced genomes are run through all kinds of computer programs in order to obtain what is used as the final `data` that biologists model. We’ve been concerned that we are not taking into account the effects of the criteria used within these different pipelines on the final analyses and inferences that researchers obtain,” remarked Huzurbazar.

In the Geosciences she works with colleagues from glaciology, sedimentology, chemical and petroleum engineering and restoration ecology. She spent 2004-5 at the Institute of Arctic and Alpine Research in Boulder, Colorado. Some of the chemical engineering and sedimentology work involves modeling distributions of sand particles or water-in-oil emulsion particles using particle or grain-size distributions. The glaciology problems are about modelling 3-dimensional data obtained from boreholes in glaciers in order to study how glaciers deform over time.


The Statistical and Applied Mathematical Sciences Institute (SAMSI) is a national institute that is forging a new syntheses of the statistical and applied mathematical sciences with disciplinary sciences to confront important data- and model-driven scientific chal¬lenges. It is based in Research Triangle Park, North Carolina.

SAMSI is a partnership of the National Science Foundation with the consortium of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill, and the National Institute of Statistical Sciences.

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