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Christian A. Johnson 111
On Leave/Away
on leave spring 2023

Clark Bowman’s favorite courses to teach have been in computational probability and statistics, and he hopes to bring a “big data” flavor to the statistics curriculum at Hamilton.

His dissertation focused on applied statistics — especially uncertainty quantification — and high-performance modeling in cellular biology. He especially enjoys using statistical tools to connect mathematical models with real data, and he is currently working on large-scale data analytics and modeling of biomarkers from wearable devices (e.g., Fitbits) in collaboration with a research group at the University of Michigan Medical School. 

Bowman has a bachelor’s degree in mathematics and a bachelor’s degree in physics from the University of Rochester and a master’s degree and doctorate in applied mathematics from Brown University. He taught for one year as a postdoctoral fellow in the Mathematics Department at the University of Michigan.

Recent Courses Taught

Statistical Modeling and Applications
Probability Theory and Applications

Select Publications

  • “Dissipative particle dynamics simulation of critical pore size in a lipid bilayer membrane.” C. Bowman, M. Chaplain, and A. Matzavinos. Royal Society Open Science, 6 (3): 181657, 2019.
  • “Bayesian uncertainty quantification for particle-based simulation of lipid bilayer membranes.” C. Bowman, K. Larson, A. Roitershtcin, D. Stein, and A. Matzavinos. In Cell Movement: Modeling and Applications. Springer, 2018.
  • “Giant acceleration of DNA diffusion in an array of entropic barriers.” D. Kim, C. Bowman, J. T. Del Bonis-O'Donnell, A. Matzaviuos, and D. Stein. Physical Review Letters, 118 (4): 048002, 2017.
  • “The potential of iterative voting to solve the separability problem in referendum elections.” C. Bowman, J. K. Hodge, and A. Yu. Theory and Decision, 77 (1): 111-124, 2014.

Professional Affiliations

Society for Mathematical Biology
Society for Industrial and Applied Mathematics
American Mathematical Society

Appointed to the Faculty

2019

Educational Background

Ph.D., Brown University
M.S., Brown University
B.S., University of Rochester

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