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Many seminars during the year will be delivered by the Purdue University Fort Wayne LDS Team on topics of interest to students, researchers, and local and global communities. The regular time of the seminars is Wednesday from 1:30pm to 2:30pm.
Title: What is Data Science?
Title: What is Data Science?
Date: Monday 6th October 2025 @ noon
Date: Monday 6th October 2025 @ noon
Alessandro Maria Selvitella
Alessandro Maria Selvitella
Department of Mathematical Sciences
Department of Mathematical Sciences
Purdue University Fort Wayne
Abstract
TBD
Title: SINDy Algorithm on Compact Riemannian Manifolds
Title: SINDy Algorithm on Compact Riemannian Manifolds
Date: Wednesday 15th October 2025 @ 1:30 pm
Date: Wednesday 15th October 2025 @ 1:30 pm
Umair Ali Wani
Umair Ali Wani
Department of Mathematics and Statistics
Department of Mathematics and Statistics
University of New Mexico
Abstract
The work involves the study of SINDy algorithm on compact Riemannian manifolds. The basic SINDy algorithm is demonstrated through examples. However, simple SINDy algorithm cannot identify dynamical systems where equations involve implicit ordinary differential equations. Consequently, SINDy-PI is explored. As a case study, an example of a particle moving on a torus is developed. It is observed that SINDy-PI can accurately identify the dynamical systems only up to a small noise.
Title: Beyond Representation Sampling: I-JEPA–Conditioned Diffusion–GANs for Medical Imaging
Title: Beyond Representation Sampling: I-JEPA–Conditioned Diffusion–GANs for Medical Imaging
Date: Wednesday 15th October 2025 @ 2:30 pm
Date: Wednesday 15th October 2025 @ 2:30 pm
Abhinay Shankar Belde
Abhinay Shankar Belde
Department of Computer Science
Department of Computer Science
Purdue University Fort Wayne
Abstract
TBD
Title: More of Less: A Rashomon Algorithm for Sparse Model Sets
Title: More of Less: A Rashomon Algorithm for Sparse Model Sets
Date: Wednesday 5th November 2025 @ 2:00 pm
Date: Wednesday 5th November 2025 @ 2:00 pm
Cesare Miglioli
Cesare Miglioli
Department of Statistics
Department of Statistics
University of Pittsburgh
Abstract
TBD
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