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Erin Conlon
Professor
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
https://www.math.umass.edu/~conlon
BostonArea Graduate Program: Statistics Master's Degree
Completely Flexible Degree (Flexible Learning With All Classes Offered Both InPerson [Evenings] and Remotely)
A 100% Remote Program is available for the Statistics M.S. Degree.
Applications for Fall 2023 are accepted on a rolling basis through June 30 (domestic students) and May 31 (international students). The priority deadline is January 10.
The M.S. degree in Statistics is offered in the Boston area at the UMassAmherst satellite campus in Newton. It is a completely flexible degree (flexible learning), with all courses offered both inperson (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.
BostonArea 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
Publications
 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 systemsbiology 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
Jeffrey Townsend
Richard Losick
Software
parallelMCMCcombine:
An R package for Bayesian methods for big data and analytics
Motif Regressor:
Regulatory motif discovery using gene expression information
Bayesian MetaAnalysis of Microarray Data
Teaching
Stat 610: Bayesian Statistics (location: Newton Mount Ida Campus (Boston Area); also offered remotely), Spring 2023
Stat 691P (locations: Newton Mount Ida Campus (Boston Area); Amherst Campus; also offered remotely): Project Seminar, Fall 2022
