# Peter Freeman's Web Page

*Baker Hall 229G*

*8-1052*

*pfreeman AT cmu DOT edu*

## Who I Am:

I am an Associate Teaching Professor in Carnegie Mellon University's
Department of Statistics & Data Science, as
well as co-director of its undergraduate program.
My primary
pedagogical interest is undergraduate research, particularly early
undergraduate research (freshmen and sophomores). I have developed and/or
am heavily involved in the following classes:

- 36-290: Introduction to Statistical Research Methodology, which
introduces early undergraduates (currently sophomores) to statistical practice.
- 36-490: Undergraduate Research, a capstone course with a focus
on academically related projects.
- 36-497: Corporate Capstone Project, a capstone course with a focus on
projects from the corporate world.

Currently I am interested in (a) quantitatively (and qualitatively)
assessing the impact of providing statistical practice opportunities to
early undergraduates, (b) providing resources that will allow other institutions to provide
early opportunities for statistical practice, and (c) developing materials
to introduce STEM students and professionals to sound statistical practice.
Outside of pedagogy, my research focuses on interesting problems in
astrostatistics. I work with a number
of professors in the department who have a long-standing interest in
the field:

I also collaborate with faculty at the McWilliams Center for Cosmology as well as astronomers and cosmologists at the University of Pittsburgh.
## Astrostatistics Projects

I am working or have worked on problems in astrostatistics:
- Galaxy Morphology
- Using random forest to detect galaxies with disturbed morphologies (paper)
- Using local two-sample testing to detect differences in morphological statistic distributions for binary classes of galaxies (e.g., high-mass v. low-mass, simulated v. real; paper)

- Photometric Redshift Estimation
- Using spectral connectivity analysis to estimate photometric redshifts (paper)
- Providing methods for estimating redshifts in the presence of selection bias (paper)

- Cosmic Microwave Background
- Checking the effect of CMB map-making parameters upon observed CMB asymmetries (paper)
- Nonparametric estimation of CMB foregrounds (with related work on CMB nongaussianities)

- Nonlinear Data Transformation
- Using diffusion map to . . .
- . . . estimate spectroscopic redshifts of SDSS galaxies and to detect outliers (paper)
- . . . estimate photometric redshifts of SDSS and DEEP2 galaxies (paper)
- . . . estimate properties of SDSS galaxies (paper)

- Supernovae
- Dark energy inference (paper)
- Inferring the velocity field of the local universe (paper)
- Semi-supervised methodology for classification (paper)

## Publicly Available Software

See my GitHub site.
## Classes at CMU

I am teaching or have taught these undergraduate classes:
- 36-149: Dietrich College Freshman Seminar: Astrostatistics: Fall 2010, Spring 2012, Spring 2014, Spring 2015, Spring 2016
- 36-220: Engineering Statistics and Quality Control: Spring 2007, Fall 2007, Spring 2009, Spring 2011, Fall 2012, Spring 2013
- 36-225: Introduction to Probability Theory: Fall 2011, Fall 2013-2018
- 36-350: Statistical Computing: Fall 2017, Spring 2019
- 36-490: Undergraduate Research: Spring 2019
- 36-494: Astrostatistics: Spring 2017
- 36-497: Corporate Capstone Project: Fall 2018, Spring 2019

Carnegie Mellon University
Department of Statistics & Data Science