Erin Conlon

Department of Mathematics and Statistics
School of Design 125J
Newton Mount Ida Campus of UMass Amherst
100 Carlson Avenue
Newton, MA 02459
Email: conlon _at_ math.umass.edu

Boston-Area Graduate Program: Statistics Master's Degree

Completely Flexible Degree (Flexible Learning With All Classes Offered Both In-Person [Evenings] and Remotely)

-A 100% Remote Program is available for the Statistics M.S. Degree.

Applications for Fall 2024 are accepted on a rolling basis through June 30 (domestic students) and May 31 (international students). Application review begins on January 10.

The M.S. degree in Statistics is offered in the Boston area at the UMass-Amherst satellite campus in Newton. It is a completely flexible degree (flexible learning), with all courses offered both in-person (evenings) and remotely. All requirements are the same as for the Amherst campus, except that students admitted to this program take courses entirely at the satellite Newton campus. Note that the degree earned is listed as the University of Massachusetts Amherst. More information is available at this link.

Boston-Area Data Science Certificate

The Certificate in Statistical and Computational Data Science is offered jointly between Statistics and Computer Science.

The Certificate can be earned completely remotely/online.

For more information, please see this link.

Education and Professional History

  • Postdoctoral Fellow, Department of Statistics, Harvard University
  • Visiting Scholar, Functional Genomics, Institute for Pure and Applied Mathematics (IPAM), University of California, Los Angeles
  • Postdoctoral Fellow, Statistical Genetics, University of Washington, Seattle
  • Ph.D. Biostatistics, University of Minnesota
  • M.S. Biostatistics, University of Minnesota
  • B.S. Mathematics, University of Wisconsin, Madison

Research and Collaborators

  • Data Science, Big Data and Analytics: I am currently developing Bayesian statistical methods for data science, big data and analytics, with the following researchers.

    Xiaojing Wang

    Zheng Wei

    Alexey Miroshnikov

  • Statistical Methods in Genomics and Bioinformatics: My research interests also include gene expression and DNA sequence analysis, Bayesian models for the analysis of genomic data and comparative genomics, with the following topics.

    • Systems biology. My current work focuses on systems-biology approaches to the study of regulatory and metabolic networks of microbes, in collaboration with the lab of Kristen DeAngelis.

    • Breast cancer gene expression studies. I am also working on statistical and bioinformatic methods for breast cancer gene expression studies in humans with the lab of Joseph Jerry.

    • Other projects involve the organisms Prochlorococcus marinus, Geobacter, and Bacillus subtilis, in collaboration with the labs of the following researchers.

      Jeffrey Blanchard

      Derek Lovley

      Richard Losick


parallelMCMCcombine: An R package for Bayesian methods for big data and analytics

Motif Regressor: Regulatory motif discovery using gene expression information

Bayesian Meta-Analysis of Microarray Data


Stat 691P: Project Seminar (locations: Newton Mount Ida Campus (Boston Area); Amherst Campus; also offered remotely), Fall 2024

Stat 610: Bayesian Statistics (location: Newton Mount Ida Campus (Boston Area); also offered remotely), Spring 2024