About the Conference

This three-day conference brings together leading researchers from academia and industry, together with graduate students and post-doctoral scholars, to discuss the latest theoretical breakthroughs and applications of Topological Data Analysis (TDA).

A central goal is to train the next generation of TDA researchers by providing a venue to present work, receive feedback, and build collaborations. TDA is evolving rapidly across theory, algorithms, and real-world applications, and our program balances cutting-edge theory with demonstrations of impact in fields ranging from machine learning to biology and network science.

Conference Themes

• • Multiparameter persistence
• • Spectral methods in TDA
• • Möbius Inversion techniques in TDA
• • Quantum Topological Data Analysis
• • Applications in Machine Learning, Network analysis etc

Organizers

Calin Chindris and Zhengchao Wan, University of Missouri-Columbia

Call for Contributed Talks and Posters

We welcome applications for contributed presentations and poster submissions. Junior researchers are especially encouraged to apply.

Use the application form below to be considered.

Apply for Contributed Talk or Poster

Acknowledgements