08/30
No seminar
Cancelled due to Idalia
Applied & Computational Mathematics Seminar
Fall 2023 ACM Seminar
Department of Mathematics, Florida State University
Seminar information
The Applied and Computational Mathematics Seminar features talks across applied mathematics, computational mathematics, data science, engineering, and related scientific applications. Faculty, postdocs, visitors, and senior Ph.D. students are welcome to present.
Schedule
15 entries09/06
-
Organization Meeting
09/13
Zecheng Zhang
A discretization-invariant extension and analysis of deep operator networks and topics in scientific machine learning
Department of Mathematics, Florida State University
09/20
Qi Feng
Entropy dissipation for general Langevin dynamics and its application
Department of Mathematics, Florida State University
09/27
SeongHee Jeong
C0 interior penalty methods for elliptic distributed optimal control problems
Department of Mathematics, Florida State University
10/04
Kourosh Shoele
Tackling Fluid-Structure Interactions in Unsteady Complex Flows
Department of Mechanical Engineering, FSU/FAMU
10/11
Hristo G. Chipilski
Beyond the Kalman Filter with Measure Transport
Department of Scientific Computing, Florida State University
10/18
Malbor Asllani
Self-organized criticality explains the emergence of irregular vegetation patterns in semi-arid regions
Department of Mathematics, Florida State University
10/25
Christopher Tam
Computational Fluid Dynamics and Computational Aeroacoustics: What are their differences?
Department of Mathematics, Florida State University
11/01
Mohammad Nooranidoost
A multiscale mathematical model for biofilm structure and viscoelasticity
Department of Mathematics, Florida State University
11/08
Seulip Lee
Edge-averaged virtual element methods for convection-dominated problems
University of Georgia
11/15
Arash Fahim
Recent Advances in the Theory of Stochastic Control
Department of Mathematics, Florida State University
11/22
No seminar
Thanksgiving Day Holiday (No Classes)
11/29
Guannan Zhang
Generative Machine Learning Models for Uncertainty Quantification
Oak Ridge National Laboratory
12/6
Mark Sussman
TBA
Department of Mathematics, Florida State University