About Me

I recently left my position as a postdoctoral researcher at Cambridge to pursue a career in industry. At Cambridge, my research centered around utilizing my broad quantitative skill set to further our understanding of the Universe through analyzing the increasingly massive astronomical data sets that are collected by modern sky surveys.

Prior to Cambridge, I was a postdoctoral fellow in the Machine Learning Department at Carnegie Mellon University, where I was a core member of the CMU-based Delphi Group and Team Lead of the forecasting development and evaluation initiative. Under the supervision of Prof. Ryan Tibshirani, my team devoted our work to developing statistical models for forecasting COVID-19 incidence in the United States in order to support and advise the Centers for Disease Control and Prevention’s COVID-19 forecasting effort and the broader national response to the pandemic. I also held a guest researcher appointment at the Flatiron Institute's Center for Computational Astrophysics in New York.

I earned a Joint Ph.D. in Statistics and Machine Learning from Carnegie Mellon University in June 2020 under the multidisciplinary supervision of Professors Larry Wasserman, Jessi Cisewski-Kehe, and Rupert Croft. My dissertation Statistical Astrophysics was devoted to a variety of problems in astrostatistics and astroinformatics, and was selected (by faculty vote) as the 2020-'21 winner of the Umesh K. Gavaskar Memorial Award for the Best Ph.D. Dissertation in Statistics and Data Science at Carnegie Mellon. Prior to earning my Ph.D., I received an M.Sc. in Machine Learning from Carnegie Mellon.

My name is pronounced kä•lən pō•lich.

Curriculum Vitae

Publications

Three-dimensional cosmography of the high redshift Universe using intergalactic absorption

C. A. Politsch, J. Cisewski-Kehe, R.A.C. Croft, and L. Wasserman
Pre-submission Inquiry approved by Nature.
Preparing to submit in full.
Webinar Talk (YouTube) Three-dimensional cosmography of the high redshift Universe using intergalactic absorption

Trend Filtering - I. A Modern Statistical Tool for Time-Domain Astronomy and Astronomical Spectroscopy

C. A. Politsch, J. Cisewski-Kehe, R.A.C. Croft, and L. Wasserman
Monthly Notices of the Royal Astronomical Society, 492(3), March 2020.
Best paper finalist in the 2020 ASA Astrostatistics Student Paper Competition. [Finalists]
Publisher arXiv Software

Trend Filtering - II. Denoising Astronomical Signals with Varying Degrees of Smoothness

C. A. Politsch, J. Cisewski-Kehe, R.A.C. Croft, and L. Wasserman
Monthly Notices of the Royal Astronomical Society, 492(3), March 2020.
Best paper finalist in the 2020 ASA Astrostatistics Student Paper Competition. [Finalists]
Publisher arXiv Software

Statistical Astrophysics: From Extrasolar Planets to the Large-scale Structure of the Universe

C. A. Politsch
Carnegie Mellon University, Ph.D. Dissertation, June 2020.
2020-'21 Winner of the Umesh K. Gavaskar Memorial Award for the Best Ph.D. Dissertation in Statistics and Data Science at Carnegie Mellon University.
CMU Thesis Archive

An Open Repository of Real-Time COVID-19 Indicators

A. Reinhart, L. Brooks, M. Jahja, A. Rumack, J. Tang, and the Delphi Research Group [58 more authors]
Proceedings of the National Academy of Sciences, 118(51), December 2021.
Publisher medRxiv Data access

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

E. Y. Cramer, E. L. Ray, V. K. Lopez, et al. [292 more authors]
Proceedings of the National Academy of Sciences, 119(15), April 2022.
A collaboration between the Reich Lab, the Delphi Research Group, the Centers for Disease Control and Prevention, and others.
Publisher medRxiv Data access

The United States COVID-19 Forecast Hub dataset

E. Y. Cramer, Y. Huang, Y. Wang, and the US COVID-19 Forecast Hub Consortium [423 more authors]
Scientific Data, 9(462), August 2022.
Publisher Data access

Mapping the Large-Scale Universe through Intergalactic Silhouettes

C. A. Politsch and R.A.C. Croft
CHANCE, 32(3), September 2019.
Publisher

Augmenting Adjusted Plus-Minus in Soccer with FIFA Ratings

F. Matano, L. F. Richardson, T. Pospisil, C. A. Politsch, and J. Qin
Journal of Quantitative Analysis in Sports, 19(1), March 2023.
Publisher arXiv Data access

The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

P. D. Aleo, K. Malanchev, S. Sharief, D. O. Jones, et al. [79 more authors]
The Astrophysical Journal Supplement Series, 266(1), May 2023.
arXiv Data access The YSE Survey

Flight of the Bumblebee: the Early Excess Flux of Type Ia Supernova 2023bee revealed by TESS, Swift and Young Supernova Experiment Observations

Q. Wang, A. Rest, G. Dimitriadis, R. Ridden-harper, et al. [40 more authors]
The Astrophysical Journal, 962(1), February 2024.
arXiv

SN2023ixf in Messier 101: the twilight years of the progenitor as seen by Pan-STARRS

C. L. Ransome, V. A. Villar, A. Tartaglia, S. J. Gonzalez, W. V. Jacobson-Galán, C. D. Kilpatrick, R. Margutti, et al. [24 more authors]
To appear in The Astrophysical Journal.
arXiv

Photometric and Spectroscopic Analysis of SN 2022oqm: Closing the Gap Between SNe-Iax and Ic-like Calcium-Rich Transients

S.K. Yadavalli, V. A. Villar, L. Izzo, Y. Zenati, et al. [53 more authors]
Submitted to The Astrophysical Journal.
arXiv

News

Postdoc at Cambridge
09/2022
I joined the the University of Cambridge as a postdoctoral research associate in the Kavli Institute for Cosmology Cambridge and the Institute of Astronomy. At Cambridge, my research will continue to focus on a variety of problems at the interface of astrophysics, statistics, and machine learning.
Paper published in PNAS
04/2022
A co-authored manuscript "Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States" (a collaboration between the Reich Lab, the Delphi Research Group, the Centers for Disease Control and Prevention, and others) was published in Proceedings of the National Academy of Sciences.
 [Publisher] [medRxiv] [COVID-19 Forecast Hub]
Paper published in PNAS
12/2021
A co-authored manuscript "An Open Repository of Real-Time COVID-19 Indicators" by the Delphi Research Group (lead authors: Alex Reinhart, Logan Brooks, Maria Jahja, Aaron Rumack, Jingjing Tang) was published in Proceedings of the National Academy of Sciences.
 [Publisher] [medRxiv] [Supplement] [Data Access]
JSM session on Cosmostatistics
08/2021
I organized a JSM 2021 session Statistical Challenges in Cosmology, in which some statistician-cosmologists, cosmologist-statisticians, and I gave an overview of this growing nexus field and some of our respective research within it.
Guest Researcher at Flatiron CCA
07/2021
I was fortunate to join the Flatiron Institute's Center for Computational Astrophysics in NYC as a Guest Researcher.
Award for Best Ph.D. Dissertation
05/2021
My Ph.D. dissertation "Statistical Astrophysics: From Extrasolar Planets to the Large-scale Structure of the Universe" was selected (by faculty vote) as the 2020-'21 winner of the Umesh K. Gavaskar Memorial Award for the Best Ph.D. Dissertation in Statistics and Data Science at Carnegie Mellon University. [Dissertation]
Preprint submitted to JQAS
01/2021
A co-authored manuscript "Augmenting Adjusted Plus-Minus in Soccer with FIFA Ratings" was submitted to the Journal of Quantitative Analysis in Sports (lead authors: Francesca Matano and Lee F. Richardson). [arXiv] [Player Rankings]
Postdoc Fellowship in the CMU Machine Learning Dept.
08/2020
I accepted an offer to join the Machine Learning Department at Carnegie Mellon University for a 1-year postdoctoral fellowship under the supervision of Ryan Tibshirani, during which I will be a core member of the CMU-based Delphi Research Group. My research will focus on developing statistical models for forecasting COVID-19 incidence in the United States to help inform a data-driven national response to the COVID-19 pandemic and future threats to public health.
Ph.D. Defense
06/2020
I successfully defended my dissertation "Statistical Astrophysics: From Extrasolar Planets to the Large-scale Structure of the Universe", earning a Joint Ph.D. in Statistics and Machine Learning from Carnegie Mellon University. [Dissertation]
Paper published in MNRAS
03/2020
My paper "Trend Filtering – I. A Modern Statistical Tool for Time-Domain Astronomy and Astronomical Spectroscopy" was published in Monthly Notices of the Royal Astronomical Society. [DOI] [GitHub]
Paper published in MNRAS
03/2020
My paper "Trend Filtering – II. Denoising Astronomical Signals with Varying Degrees of Smoothness" was published in Monthly Notices of the Royal Astronomical Society. [DOI] [GitHub]
Paper Award
01/2020
My manuscript "Trend Filtering: A Modern Statistical Tool for Time-Domain Astronomy and Astronomical Spectroscopy" was selected as a finalist for the best paper in the ASA Astrostatistics Student Paper Competition, sponsored by the Astrostatistics Interest Group.
Finalists: Josh Speagle (Harvard), Collin Politsch (CMU), Matt Ho (CMU), Oliver Philcox (Princeton), Richard Feder (Caltech).
Article published in CHANCE
09/2019
I wrote an article, titled "Mapping the Large-Scale Universe through Intergalactic Silhouettes", for CHANCE magazine's special issue on astrostatistics. [Article]
Surname change
03/2019
I changed my surname to Politsch to honor my late mother, Carol Politsch.
Hackathon podium
10/2018
Three of my classmates and I took 2nd in The Data Open at CMU hosted by Citadel and Correlation One (300+ applications, ~125 selected to compete).
Internship at Uber HQ
06/2018 - 08/2018
I interned as a data scientist at Uber Headquarters in San Francisco during the summer of 2018. While there, I completed an end-to-end project which culminated in a new personalized ranking and recommendation algorithm for the Uber Eats iOS/Android home feed. The algorithm showed significant improvement in both offline evaluation and online A/B testing over their state-of-the-art algorithm used in the app to that point and was subsequently launched as its replacement.
Hackathon press release
11/2017
Carnegie Mellon detailed some of our hackathon successes in a press release. [Press Release]
Hackathon podium
09/2017
Three of my classmates and I took 2nd place in the 2017 NBA Hackathon (900+ applications, ~200 selected to compete). [Announcement] [Recap]
Hackathon podium
09/2017
Three of my classmates and I took 2nd place in The Data Open at CMU hosted by Citadel and Correlation One (550+ applications, ~125 selected to compete).
Hackathon podium
05/2017
Three of my classmates and I took 3rd place in the second annual Google BrainHub Neurohackathon, hosted by the Machine Learning Department at Carnegie Mellon University. [Press Release] [Live Coverage]

Contact

Press Inquiries / Collaborations / General Questions

Images

Some Snapshots from my Journey
CMU team holding up a giant check for $20,000.Collin holding his golden retriever like a baby.
Blue Waves 3 overlapping blue waves.