Adele Cutler Ph.D.

Mathematics and Statistics

Emeritus Professor


Adele Cutler

Contact Information

Email: adele.cutler@usu.edu

Educational Background

PhD, Statistics, U.C. Berkeley, 1988
MS, Statistics, U.C. Berkeley, 1984
BS, Mathematics, Auckland University, 1983
Waikato University, 1979

Biography

My undergraduate degree is from the University of Auckland and my PhD is from UC Berkeley.

Teaching Interests

Introductory statistics for quantitative literacy. Statistical learning and data mining. Introduction to R. Statistical computing.

Research Interests

Data science, statistical learning, data mining, statistical computing, Random Forests, Archetypal Analysis.

Awards

Research Catalyst Award, 2009

Utah State University

College of Science Teacher of the Year, 1998

USU College of Science

Research Award, 1998

USU Department of Mathematics and Statistics

Teacher of the Year, 1998

USU Department of Mathematics and Statistics


Publications | Abstracts

  • Wengreen, H., Corcoran, C.D, Cutler, A., Munger, R.G, Quach, A., Tschanz, J.T, Ward, R.E, (2012). Erythrocyte omega-3 fatty acid concentrations and cognitive function: The Cache County Study on Memory and Aging. Alzheimer’s & Dementia *
  • Wengreen, H., Quach, A., Cutler, A., Munger, R.G, Corcoran, C.D, (2012). Whole-grain intake and risk of all-cause mortality among elderly men and women: the Cache, County Study on Memory, Health and Aging. The FASEB Journal *

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | Books

      Publications | Book Chapters

    • Cutler, A., Cutler, D., Stevens, J.R, (2012). Random Forests: Ensemble Machine Learning, Methods and Applications. Springer
    • Cutler, A., Cutler, D., Stevens, J.R, (2009). Tree Based Methods: High-Dimensional Data Analysis in Oncology, Applied Bioinformatics and Biostatistics in Cancer Research. Springer
    • Stevens, J.R, Cutler, A., (2006). Random Forests for Microarrays: DNA Microarrays, Part B: Databases and Statistics, (Methods in Enzymology). Academic Press
    • Cutler, A., Corcoran, C.D, Toone, L., (2005). Bagging: Encyclopedia of Statistics in Behavioral Science. Wiley & Sons *
    • Cutler, A., (2005). Random Forests. Encyclopedia of Statistics in Behavioral Science

    An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

    Publications | Journal Articles

    Academic Journal

    • Gaona-Partida, P., Yeh, C., Sun, Y., Cutler, A., (2024). Random forests regression for soft interval data. Communications in Statistics - Simulation and Computation, 1-20.
    • Rhodes, J., Cutler, A., Moon, K., (2023). Geometry- and accuracy-preserving random forest proximities. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:9, 10947 - 10959.
    • Zaman, T., Kulyukin, V.A, Cutler, A., (2016). Text Skew Detection in Printed Text Images Relying on 2D Haar Wavelets. Journal of Graphics, Vision and Image Processing (GVIP), 16:1, 41-50.
    • Wengreen, H., Munger, R.G, Cutler, A., Quach, A., Bowles, A., Corcoran, C.D, Tschanz, J.T, Norton, M.C, Welsh-Bohmer, K., (2013). Prospective study of dietary approaches to stop hypertension- and mediterranean-style dietary patterns and age-related cognitive change: The Cache County Study on Memory, Health and Aging. American Journal of Clinical Nutrition, 98:5, 1263-1271. doi: 10.3945/ajcn.112.051276
    • Cutler, A., (2010). Remembering Leo Breiman. Annals of Applied Statistics, 4:4, 1621–1633.
    • Goldstein, B.A, Hubbard, A.E, Cutler, A., Barcellos, L.F, (2010). An application of Random Forests to a genome-wide association dataset: methodological considerations & new findings. BMC genetics, 11:1, 49.
    • Cutler, D., Edwards, T.C, Beard, K.H, Cutler, A., Hess, K.T, Gibson, J., Lawler, J.J, (2007). Random Forests for Classification in Ecology. Ecology, 88:11, 2783-2792.
    • Torres, A.R, Sweeten, T.L, Cutler, A., Bedke, B.J, Fillmore, M., Stubbs, E.G, Odell, D., (2006). The association and linkage of the HLA-A2 class I allele with autism. Human Immunology, 67:4-5, 346-351.
    • Odell, D., Maciulis, A., Cutler, A., Warren, L., McMahon, W., Coon, H., Stubbs, G., Henley, K., Torres, A., (2005). Confirmation of the Association of the C4B Null Allele in Autism. Human Immunology, 66:2, 140-145.
    • Truong, Y., Lin, X., Beecher, C., Cutler, A., Young, S., (2004). Learning a complex metabolomic dataset using random forests and support vector machines. Knowledge Discovery and Data Mining
    • Xie, Y., Chou, L., Cutler, A., Weimer, B., (2004). Expression profiling Lactococcus lactis ssp. lactis IL1403 during environmental stresses with DNA macroarray. Applied and Environmental Microbiology, 70:11, 6738-6747.
    • Cutler, D., Brown, L., Powell, J.A, Bentz, B., Cutler, A., (2003). Identifying ‘Redtops’: Classification of Satellite Imagery for Tracking Mountain Pine Beetle Progression through a Pine Forest. Computing Science and Statistics, 35, 711–728.
    • Xie, Y., Cutler, A., Weimer, B., Parfionovas, A., (2003). Statisical Methods for Spot Detection with Macroarray Data. Computing Science and Statistics, 35, 490–505.
    • Torres, A.R, Maciulis, A., Stubbs, E.G, Lainhart, J., Cutler, A., Odell, J.D, (2002). The Transmission Disequilibrium Test suggests that HLA-DR4 is linked in Autism Spectrum Disorder. Human Immunology, 63:4, 311–316.
    • Cutler, A., Zhao, G., (2001). PERT – Perfect Random Tree Ensembles. Computing Science and Statistics, 33, 490-497.
    • Cutler, D., Cutler, A., (2000). Minimum Hellinger Distance Estimation for the Beta Distribution. Communications in Statistics, 29:7, 1487-1509.
    • Stone, E., Cutler, A., (1996). Archetypal analysis of spatio-temporal dynamics. Physica D, 90, 209-224.
    • Stone, E., Cutler, A., (1996). Introduction to archetypal analysis of spatio-temporal dynamics. Physica D, 96, 110-131.
    • Cutler, A., Cordero–Brana, O., (1996). Minimum Hellinger Distance Estimation for Finite Mixture Models. Journal of the American Statistical Association, 91:436, 1716-1723.
    • Cutler, A., Baritompa, W., (1994). Accelerations for Global Optimization Covering Methods Using Second Derivatives. The Journal of Global Optimiza- tion, 4, 329-341.
    • Cutler, A., Breiman, L., (1994). Archetypal analysis. Technometrics, 36:4, 338-347.
    • Cutler, A., (1993). A branch and bound algorithm for constrained least squares. Com- munications in Statistics - Simulation and Computation, 22:2, 305-321.
    • Cutler, A., Breiman, L., (1993). A deterministic algorithm for global optimization. Mathematical Programming, 58:2, 179-199.
    • Whindham, M., Cutler, A., (1992). Information Ratios for Validating Mixture Analysis. Am. Statistical Assoc, 87, 1–188.

    An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

    Publications | Technical Reports

    Other Reports

    • Moisen, G.G, Cutler, D., Cutler, A., (1990). Maximum Likelihood Estimation for Heteroscedastic Linear Models. Utah State University Department of Mathematics and Statistics Technical Report Series

    An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

    Publications | Other

    Magazine/Trade Publications

    • Cutler, D., Grange, E.V, Hampton, V.L, Cutler, A., Langdon, T.P, Ryan, M.T, (2005). Analysis of Factors Relating to Success on the CFP® Certification Examination. Financial Services Review

    Other

      An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

      Teaching

      STAT 5050 - Introduction to R, Spring 2020
      STAT 6950 - Directed Reading and Conference, Fall 2019
      STAT 5050 - Introduction to R, Fall 2019
      STAT 1040 - Introduction to Statistics, Fall 2019
      STAT 6950 - Directed Reading and Conference, Fall 2018
      STAT 5810, 6910 - Seminar in Statistics, Fall 2018
      STAT 5810 - Topics in Statistics, Fall 2018
      STAT 6910 - Seminar in Statistics, Spring 2018
      STAT 5810 - Topics in Statistics, Spring 2018
      STAT 1040 - Introduction to Statistics, Fall 2017
      STAT 5810 - Topics in Statistics, Fall 2017
      STAT 5810, 6910 - Seminar in Statistics, Spring 2017
      STAT 6910 - Seminar in Statistics, Spring 2017
      STAT 6950 - Directed Reading and Conference, Fall 2016
      STAT 5100 - Linear Regression and Time Series, Fall 2016
      STAT 5100 - Linear Regression and Time Series, Fall 2016
      STAT 5820, 6910 - Seminar in Statistics, Fall 2016
      STAT 5810 - Topics in Statistics, Fall 2016
      STAT 5940 - Directed Reading and Conference, Summer 2016
      STAT 1045 - Introduction to Statistics with Elements with Algebra (QL), Spring 2016
      STAT 6910 - Seminar in Statistics, Spring 2016
      STAT 6910 - Seminar in Statistics, Spring 2016
      STAT 6910 - Seminar in Statistics, Spring 2016
      STAT 5810 - Topics in Statistics, Fall 2015
      STAT 5820, 6910 - Topics in Statistics, Fall 2015
      STAT 6910 - Seminar in Statistics, Spring 2015
      STAT 6910 - Seminar in Statistics, Spring 2015
      STAT 5820 - Topics in Statistics, Spring 2015
      STAT 5810 - Topics in Statistics, Fall 2014
      STAT 5820 - Topics in Statistics, Fall 2014
      STAT 1040 - Introduction to Statistics, Spring 2014
      STAT 6910 - Seminar in Statistics, Spring 2014
      STAT 6650 - Stat Learning: Multivariate Stat Analysis for Bioinformatics, Data Mining, and Machine Learning, Fall 2013
      STAT 5810 - Topics in Statistics, Fall 2013
      STAT 7810 - Topics in Statistics (Topic), Fall 2013
      STAT 6550,7810 - Statistical Computing, Spring 2013
      STAT 1040 - Introduction to Statistics, Fall 2012
      STAT 5810 - Topics in Statistics, Fall 2012
      STAT 6810 - Topics in Statistics (Topic), Fall 2012
      STAT 6810 - Topics in Statistics (Topic), Fall 2012
      MATH 7990 - Continuing Graduate Advisement, Summer 2012
      MATH 6910 - Directed Reading and Conference, Summer 2012
      MATH 7970 - Dissertation Research, Summer 2012
      STAT 6970 - Thesis and Research, Summer 2012
      STAT 6650,7820 - Stat Learning: Multivariate Stat Analysis for Bioinformatics, Data Mining, and Machine Learning, Spring 2012
      stat 1040 - Intro to statistics (QL), Fall 2011

      Graduate Students Mentored

      Jadon Wagstaff, Mathematics & Statistics, August 2019
      Sharad Jones, Mathematics & Statistics, August 2017
      Christopher Beckett, Mathematics & Statistics, August 2017 - December 2018
      Breckell Soifua, Mathematics & Statistics, September 2016 - May 2018
      Joshua Young, Mathematics & Statistics, August 2015 - May 2017
      Anna Quach, Mathematics & Statistics, August 2012 - May 2017
      Willis Barton, Mathematics & Statistics, August 2014 - December 2016
      Jenny Clements, Mathematics & Statistics, May 2015 - March 2016
      Chunyang Li, Mathematics & Statistics, August 2011 - May 2013
      Anna Quach, Mathematics & Statistics, August 2010 - May 2012
      Rong Xia, Mathematics & Statistics 2009
      Andrejus Parfionovas, 2009
      Guohua Zhao, Mathematics & Statistics, August 1996 - May 2000
      Olga Cordero–Brana, Mathematics & Statistics, August 1989 - May 1994