Sean P. Carney

Sean P. Carney is an Assistant Professor of Mathematics at Union College, focusing on applied and computational mathematics. His roles include teaching courses in differential equations, partial differential equations, and numerical methods, while leading research in multiscale and stochastic modeling, PDE-constrained optimization, and turbulent flow dynamics.

• Education: Ph.D. in Mathematics from the University of Texas at Austin (2020), advised by Björn Engquist; B.S. in Mathematics from the University of Michigan, Ann Arbor (2014).
• Prior Experience: Postdoctoral Research Fellow at George Mason University’s Center for Mathematics and Artificial Intelligence; Hedrick Assistant Adjunct Professor at UCLA (2020–2023); Graduate Research Assistant at Lawrence Berkeley National Lab (2018–2019).

Carney’s research centers on multiscale and stochastic modeling, with applications in transport and mixing in turbulent flows, homogenization theory, and optimization under uncertainty. His work combines numerical analysis with physical modeling to solve complex problems in PDE-constrained optimization and fluid dynamics.

Recent publications highlight his contributions to numerical homogenization, chaotic electroconvective flow modeling, and liquid-liquid phase separation in confined systems. These studies span fluid dynamics, computational physics, and applied mathematics, often involving collaborations with institutions like UCLA, UT Austin, and Lawrence Berkeley National Lab.

• Scientific Awards:
  • Editors' Suggestion, Physical Review Fluids (2020)

Carney has mentored students in the UCLA Computational and Applied Mathematics REU program and the Cal-State/UCLA Summer Bridge Program. His teaching spans differential equations, numerical methods, and advanced PDE courses at Union College and UCLA.