

#120 - Iolo Jones: Riemannian Diffusion Geometry, Geometric Data Analysis, Markov Chains
Nov 29, 2024
Iolo Jones, a PhD student at Durham University, explores the cutting-edge field of geometric data analysis. He reveals how diffusion geometry surpasses traditional methods in analyzing tumor histology data. The conversation dives into the challenges of high-dimensional data, the importance of geometric properties in medical diagnostics, and the innovative integration of AI in data analysis. Jones also shares insights into the trials of research, the creative aspects of mathematics, and the future of complex mathematical concepts impacting real-world applications.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10
Intro
00:00 • 2min
Navigating Three-Dimensional Data Complexity
02:14 • 26min
Exploring Diffusion and Persistence Homology
27:44 • 15min
Navigating Research: Embracing Blind Alleys in Scientific Inquiry
42:48 • 2min
Dynamic Geometric Data Analysis
45:07 • 18min
Optimizing Computation in High Dimensions
01:03:01 • 5min
Exploring Diffusion Geometry and Information Dynamics
01:08:06 • 8min
The Geometry of Synthetic Data
01:15:46 • 9min
Independent Learning in Mathematics
01:24:54 • 7min
Reflections on Complex Mathematics and Future Conversations
01:31:41 • 2min