John Whelan

Professor

School of Mathematics and Statistics

College of Science

jtwsma@rit.edu

585-475-5083

Office Hours

Via zoom https://rit.zoom.us/j/96378996388 Tue/Fri 10:00-11:00am or by appointment (send email to jtwsma@rit.edu)

Office Location

LAC-2063

Office Mailing Address

RIT School of Mathematical Sciences 85 Lomb Memorial Drive Rochester, NY 14623

John Whelan

Professor

School of Mathematics and Statistics

College of Science

Education

BA, Cornell University; Ph.D., University of California at Santa Barbara

jtwsma@rit.edu

585-475-5083

Personal Links

Personal Website

ORCID

Twitter

Areas of Expertise

Gravitational Wave Data Analysis

Gravitational Waves

Gravitational Physics

Statistical Signal Processing

Bayesian Inference

Bayesian Statistics

Mathematical Modeling

Astrophysics

Astrophysical Sciences and Technology

Computational Relativity and Gravitation

Currently Teaching

ASTP-612

Mathematical and Statistical Methods for Astrophysics

3 Credits

This course provides an introduction to the applied mathematical and statistical tools used frequently in astrophysics including modeling, data reduction, analysis, and computational astrophysics. Topics will include Special Functions, Differential Equations, Probability and Statistics, and Frequency Domain Analysis.

ASTP-711

Advanced Statistical Methods for Astrophysics

3 Credits

This is an advanced course in statistical inference and data analysis for the astrophysical sciences. Topics include Bayesian and frequentist methods of parameter estimation, model selection and evaluation using astrophysical data. Specific applications, such parameter estimation from gravitational wave signals, or analysis of large data sets from imaging, spectroscopic or time domain surveys will be discussed. Computational methods including Markov Chain Monte Carlo, with other topics such as machine learning, and time series analysis included at the discretion of the instructor.

ASTP-790

Research & Thesis

1 - 3 Credits

Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

ASTP-791

Continuation of Thesis

0 Credits

Continuation of Thesis

ASTP-890

Research & Thesis

1 - 6 Credits

Dissertation research by the candidate for an appropriate topic as arranged between the candidate and the research advisor.

ASTP-891

Continuation of Thesis

0 Credits

Continuation of Thesis

MATH-251

Probability and Statistics

3 Credits

This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.

MATH-381

Complex Variables

3 Credits

This course covers the algebra of complex numbers, analytic functions, Cauchy-Riemann equations, complex integration, Cauchy's integral theorem and integral formulas, Taylor and Laurent series, residues, and the calculation of real-valued integrals by complex-variable methods.

STAT-345

Nonparametric Statistics

3 Credits

This course is an in-depth study of inferential procedures that are valid under a wide range of shapes for the population distribution. Topics include tests based on the binomial distribution, contingency tables, statistical inferences based on ranks, runs tests and randomization methods. A statistical software package is used for data analysis.

STAT-753

Nonparametric Statistics and Bootstrapping

3 Credits

The emphasis of this course is how to make valid statistical inference in situations when the typical parametric assumptions no longer hold, with an emphasis on applications. This includes certain analyses based on rank and/or ordinal data and resampling (bootstrapping) techniques. The course provides a review of hypothesis testing and confidence-interval construction. Topics based on ranks or ordinal data include: sign and Wilcoxon signed-rank tests, Mann-Whitney and Friedman tests, runs tests, chi-square tests, rank correlation, rank order tests, Kolmogorov-Smirnov statistics. Topics based on bootstrapping include: estimating bias and variability, confidence interval methods and tests of hypothesis.

In the News

June 12, 2023

Gravitational-wave detectors start next observing run to explore the secrets of the universe

According to scientists from across the globe—including those working on the project from RIT—this observing run by the LIGO-Virgo-KAGRA (LVK) collaboration features upgraded instruments, new and even more accurate signal models, and more advanced data analysis methods.
January 27, 2023

RIT scientists reach a milestone in the search for continuous gravitational waves

Scientists on the hunt for a previously undetected type of gravitational waves believe they are getting close and have refined techniques to use in upcoming observational runs. Researchers from the LIGO-Virgo-KAGRA Collaboration outlined the most sensitive search to date for continuous gravitational waves from a promising source in a paper recently published in the Astrophysical Journal Letters.
November 21, 2022

Dozens of RIT researchers included on Stanford University’s list of the world’s top 2% of scientists

Numerous Rochester Institute of Technology faculty, professors emeriti, and postdoctoral researchers were recognized as top-cited scientists in their fields, according to a Stanford University study published by Elsevier.

More News

August 24, 2022

Whelan named co-chair of LIGO-Virgo-KAGRA group

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