His story: Born and raised in Cincinnati, Ohio, Tim completed his undergraduate studies at The Ohio State University where he majored in mathematics with a minor in statistics and economics. For as long as he can remember, Tim has always loved mathematics and problem solving, and he sought a career where he could apply his math skills to the real world.
Tim also had many mentors who guided him towards a career in statistics. His high school math teachers, Mark Lapille and Rick Lovins, played a crucial role in planting the seed of interest. Later at Ohio State, Dr. Laura Kubatko and Dr. Steve MacEachern helped to better introduce him to statistics and statistical research.
When it came to choosing a graduate school, Tim wanted to go somewhere that would allow him to engage in interdisciplinary, collaborative work. Knowing that the University of Michigan is a large institution with excellent departments across a wide variety of fields, he was excited to work with the top tier interdisciplinary teams here at the University.
His interests: In terms of Statistics, Tim’s interests primarily lie in the areas of experimental design, causal inference, intensive longitudinal data, and reinforcement learning. Tim recently graduated from the U-M Statistics Ph.D. program and his thesis titled “Design and Analysis of Sequential Randomized Trials with Applications to Mental Health and Online Education” centered on a novel experimental design useful for answering important causal questions in mobile health and online courses.
His advice for future students of Statistics: As someone who has loved math all of his life, Tim would definitely encourage people with similar interests as him to study statistics: “If you love math and want to apply your math skills to impact the real world, study statistics. If you want the skills to understand our increasingly data-driven world, and you want those skills to be foundational and rigorous, study statistics.”
And yet, Tim also acknowledges that there are real challenges that accompany the field. As statistics is constantly evolving with new technology and methods, it can be hard to quickly develop all the necessary skills to have a comprehensive grasp on the field, while also finding a specialization.
“A statistician has to cover a lot of ground. We must understand and prove rigorous theory, develop and use novel methods, code and utilize new-age computational resources to implement methods, apply the method to real data, and understand the application area of the data. It was challenging to develop skills in all of these areas while simultaneously finding my niche.”
What’s next for Tim?: Tim will be working as a consultant for a year and applying to professorships in the fall!