Conference: Heat Kernels and Stochastic Analysis
- Institution
- Purdue University, IN
- Principal investigator
- Jing Wang
- Funding
- $32K
- Duration
- 2026–2027
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Abstract
This project supports U.S.-based researchers to participate in the five-day conference Heat Kernels and Stochastic Analysis, to be held at Aarhus University in Denmark from June 29 to July 3, 2026. The event will bring together leading experts in stochastic analysis and heat kernel methods to share recent advances, discuss connections between analysis and probability, and develop new collaborations on diffusion and stochastic dynamics on complex spaces. The conference will promote international collaboration and offer strong visibility for graduate students and postdoctoral researchers, helping connect researchers across career stages and areas of expertise. Heat semigroups provide a natural framework connecting probability, geometry, and functional analysis. Recent work has linked heat kernel methods to curvature-dimension conditions, sub-Riemannian geometry, spectral theory, and analysis on singular or rough spaces. At the same time, stochastic techniques such as SPDEs and rough path theory have advanced the study of nonlinear phenomena and scaling limits in complex systems. The conference will highlight both foundational developments and new applications, with particular emphasis on the interaction between probabilistic and analytic approaches. The website of the conference is: https://conferences.au.dk/saa-heat-kernels-2026. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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