TGDA@OSU: Discovering Structure, Shape, and Dynamics in Data
This project will advance the methodological and theoretical foundations of data analytics by considering the geometric and topological aspects of complex data from mathematical, statistical and algorithmic perspectives, thus enhancing the synergy between the Computer Science, Mathematics, and Statistics communities.
Furthermore, this project will benefit a range of impactful scientific areas including medicine, neuronanatomy, machine learning, geographic information systems, mechanical engineering designs, and political science. The research products will be implemented and disseminated through software packages and tutorials, allowing widespread application by industrial and academic practitioners.
Through this project, the PIs will develop curricula for cross-disciplinary, undergraduate and graduate education. Additionally, this project aims to develop partnerships with the Translational Data Analytics and the Mathematical Biosciences Institutes at OSU, as well as other internal and external research and education centers.
The TGDA@OSU TRIPODS team is composed of Tamal Dey, Matthew Kahle, Sebastian Kurtek, Facundo Mémoli, David Sivakoff and Yusu Wang.
Areas of Expertise
Tamal Dey (CSE): algorithms, computational geometry and topology, topological data analysis, surface reconstruction, mesh generation, geometric modeling.
Matthew Kahle (Math): stochastic topology, topological statistical mechanics, combinatorics.
Sebastian Kurtek (Stats): statistical shape analysis, functional data analysis, statistics on manifolds, computational statistics.
Facundo Memoli (Math and CSE ): shape analysis, topological data analysis, applied metric geometry, networks.
David Sivakoff (Stats and Math): probability theory, stochastic processes on large finite graphs, percolation models and particle systems.
Yusu Wang (CSE): discrete and computational geometry, computational and applied topology, geometric algorithms, and topological data analysis.