Daniel Harnett

Daniel Harnett is Professor and Chair of the Department of Mathematical Sciences at the University of Wisconsin-Stevens Point, holding a Ph.D. in Probability from the University of Kansas. He teaches undergraduate courses including Differential Equations, Elementary Statistical Methods, and Introduction to Linear Algebra.

Educational background:

• Ph.D. in Probability, University of Kansas

Research Interests:
Dr. Harnett specializes in stochastic analysis with core expertise in stochastic processes and Malliavin calculus. His work investigates theoretical properties of self-similar Gaussian processes, focusing on symmetric stochastic integrals, decomposition theorems, and non-Markovian frameworks to advance probabilistic modeling and stochastic calculus.

Publication Trends:
His 2017-2019 publications demonstrate concentrated research on self-similar Gaussian processes, revealing methodological innovations in symmetric integration techniques and asymptotic behavior analysis. These contributions bridge probability theory with functional analysis, particularly in fractional process modeling and limit theorem applications.

Scientific Awards:
No awards or honors are documented in the available information.

Advising and Grants:
The provided materials contain no details regarding student supervision, research grants, or funded projects.