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: M.S. Option in Statistics
The M.S. option in Statistics is also offered in the Boston area at the UMass-Amherst satellite campus in Newton, with entirely evening classes. 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.
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.
- 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.
- Climate change and systems biology.
My current work focuses on climate change and 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.
An R package for Bayesian methods for big data and analytics
Regulatory motif discovery using gene expression information
Bayesian Meta-Analysis of Microarray Data
Stat 691P (location: Newton Mount Ida Campus (Boston Area)): Project Seminar, Fall 2021
Stat 691P (location: Newton Mount Ida Campus (Boston Area)): Project Seminar, Fall 2020
Stat 625 (location: Newton Mount Ida Campus (Boston Area)): Regression Modeling, Fall 2019
Stat 525: Regression Analysis, Spring 2019
Stat 516: Statistics II, Fall 2018
Stat 526: Design of Experiments, Spring 2018
Stat 516: Statistics II, Spring 2018
Stat 697B: Bayesian Statistics, Fall 2017