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     Brian Steele

Rank: Professor
E-mail: brian.steele@umontana.edu
Office: Math 314
Phone: Office:  (406) 243-5396
Department:  (406) 243-5311
Fax:  (406) 243-2674
Address:   Department of Mathematical Sciences
University of Montana
32 Campus Dr. #0864
Missoula, MT 59812-0864, USA

Research Interests:

Classification and discriminant analysis, bootstrap methods, generalized linear models, linear mixed models, generalized linear mixed models, spatial statistics, ecological applications of statistics.

Education:

Ph.D., University of Montana, 1995.
M.S., Statistics, Oregon State University , 1987.

Opportunities:

HP is interviewing at UM for a data scientist position.

Data Science:

The Department of Mathematical Sciences has developed an innovative, industry-centered program to train students in data science. Our focus, which is significantly different from other Universities that also have begun data science programs, is to focus on teaching data analytics and theory for real big data problems. Our goal is to produce graduates that have faced the challenges of big data with real problems and are ready to be productive employees. We want our graduates to be productive on the first day of the job.

We offer four courses directly aimed at big data:
  1. Practical Big Data Analytics. A methods course taught in a lab format with a very heavy emphasis on programming (90% Python, 10% R) and big data algorithms such as Map/Reduce. Students program all of the algorithms they use so that they understand whatís going on.
  2. Theoretical Big Data Analytics and Near Real-Time Computation Algorithms. A theory course aimed at providing students with the knowledge and understanding necessary for innovation and creating new algorithms.
  3. Big Data Analytic Projects. Practical experience in solving real problems brought by technology companies. The next paragraph explains more.
  4. Cognitive Computing. Aimed at understanding the capabilities and limitations of IBM Watson.
The Big Data Analytic Projects course was taught for the first time Spring semester 2014. Problems were brought to us from industry and academia. In brief, these were
  1. Estimate of inter- and intra-company teleconference usage from incomplete log files. Brought by Dan Cripe, ATG.
  2. Investigation and development of algorithms for predictive analytics. Brought by Kegan Rabil, GCS.
  3. Develop software to estimate the height of the atmospheric inversion layer from radiosonde transmissions. Brought by Jennifer Fowler, NASA Outreach.
  4. Analyze the relationship between mobility, pain, and barriers encountered by persons with disabilities using data collected by personal data recorders. Brought by Craig Ravesloot, U Montana Rural Institute.
If your company has a problem and would like to discuss contributing it to the class, please contact me at brian.steele@umontana.edu or 406-243-5396. We will work with you and try to produce the most valuable solution possible.

Are there any other reasons to come to Missoula and the University of Montana to study big data? Yes:
  1. Missoula is the best place in Montana for technology businesses, itís one of 50 Google eCities, and it's ranked fifth in the country among cities with a population of less than 250,000 for its number of high-tech launches. Plus, the skiing, hiking, mountain biking, kayaking, floating, hunting, and fishing is great.
  2. The University has a Certificate program in the works for big data.
  3. Other departments offer data science course as well.
You can learn more from the official webpage: http://www.umt.edu/datascience/

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