D. Michael Senter

D. Michael Senter

Research Statistician Developer

SAS Institute

Biography

Mathematical modeling, data analysis, and machine learning have been the major themes of Michael’s academic endeavors. The through line of his career has been the utilization of coding to solve computationally complex problems.

Michael enjoys mentoring and teaching. His teaching philosophy is based on his own experience - that a passion for math and computer science can be cultivated through active learning and emphasizing small victories.

Michael is originally from Nuremberg, Germany where he attended the Neues Gymnasium Nuernberg, a school following the humanist tradition of education. He now lives in Lexington with his family, where he enjoys travelling, collecting books, and reading nerdy webcomics in his spare time.

Interests

  • Data Cleaning and Preparation
  • Missing Data Methods
  • Big Data and Data Analytics
  • Causal Inference

Education

  • PhD in Applied Mathematics, 2021

    University of North Carolina at Chapel Hill

  • Grad. Certificate in Bioinformatics and Computational Biology, 2021

    University of North Carolina at Chapel Hill

  • Grad. Certificate in BD2K Data Science, 2021

    University of North Carolina at Chapel Hill

  • BSc in Mathematics, 2015

    University of Utah

Recent Posts

Takeaways from 'On the uses and abuses of regression models'

This weekend I found an interesting new preprint by Carlin and Moreno-Betancur on arxiv titled “On the Uses and Abuses of Regression Models” so I had to check it out.

Calling R From SAS

The statistics literature is filled with example code and sample data in R. Sometimes I find myself wanting to work through some provided sample data and compare the output from R with SAS code.

Automatic Suspend in Fedora 38

For a while now I’ve recycled an old iMac running Fedora Workstation as a simple homeserver. It’s been working well in the past, but just now with the EOL of Fedora 37 did I get around to updating from Fedora 36 to Fedora 38.

Reproducibility by Sharing Code

Whenever I speak with students, I emphasize the need to share as much code and data as is feasible to enable reproduciblity. The fact that a large amount of research is not reproducible is a big issue that has gotten a lot of traction in the past two decades since Ioannidis published his influental paper.

Some Basic SQL Joins

A non-technical friend recently asked me for help with a merge problem. They had two separate data pulls of electronic medical records based on specific study parameters. The set of people in the database who fit the study parameters changed in between the data pulls, for example by having people age into our out of a study, or by having new diagnoses added to their records that cause them to either be newly included or excluded.

Recent & Upcoming Talks

CMSRP Data Analytics Workshop

This 1-hour workshop is intended to help funded CMSRP students prepare for their summer research project. Current best practices in data analytics will be discussed, with emphasis on the pre-analysis phase of the research cycle.

Dissertation Defense

All organisms must deal with fluid transport and interaction, whether it be internal, such as lungs moving air for the extraction of …

Basics of Web Scraping with Python

Data acquisition is a key step in research. In this workshop, we will consider how to effectively access publicly available data sets. …

Thesis Proposal

Please join me as I present the work I have done so far in my graduate career and discuss avenues for future study.

Recent Publications

Quickly discover relevant content by filtering publications.

Family History And Chronic Medical Conditions Associated With Sudden Death Among Working Age Adults

Background Sudden death accounts for 10% of deaths in the United States. Prior research has focused on sudden death in older victims, leaving much unknown about risk factors for younger, working age adults.

Former Incarceration As A Risk Factor For COVID-19 Associated Sudden Death

Background In the United States, former incarceration is a risk factor for chronic conditions and sudden death (SD) due to poor healthcare continuity after release and lack of community support. During the COVID-19 pandemic, all-cause mortality increased, and preexisting risk factors and social limitations of having an incarceration history were exacerbated.

Housing Insecurity: Effects on Sudden Death and Interaction with Mental Illness

Background Housing insecurity is a powerful social determinant of health that is associated with increased all-cause mortality. The health consequences of and contributors to housing insecurity are poorly studied, which makes preventative care elusive for this population.

Immersed Boundary Simulations and Tools for Studying Insect Flight and Other Applications

All organisms must deal with fluid transport and interaction, whether it be internal, such as lungs moving air for the extraction of oxygen, or external, such as the expansion and contraction of a jellyfish bell for locomotion.

A semi-automated finite difference mesh creation method for use with immersed boundary software IB2d and IBAMR

Numerous fluid-structure interaction problems in biology have been investigated using the immersed boundary method. The advantage of …

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