NLM DIR Seminar Schedule

Abstract:

Over the past decade, deep learning has been remarkably successful at solving a massive set of problems on data types including images and sequential data. This success drove the extension of deep learning to other discrete domains such as sets, point clouds, graphs, 3D shapes, and discrete manifolds. While many of the extended schemes have successfully tackled notable challenges in each domain, the plethora of fragmented frameworks have created or resurfaced many long-standing problems in deep learning such as explainability, expressiveness and generalizability. Moreover, theoretical development proven over one discrete domain does not naturally apply to the other domains. Finally, the lack of a cohesive mathematical framework has created many ad hoc and inorganic implementations and ultimately limited the set of practitioners that can potentially benefit from deep learning technologies.

This talk introduces the foundation of topological deep learning, a rapidly growing field that is concerned with the development of deep learning models for data supported on topological domains such as simplicial complexes, cell complexes, and hypergraphs, which generalize many domains encountered in scientific computations including images and sequence data. It introduces the main notions while maintaining intuitive conceptualization, implementation and relevance to a wide range of practical applications. It also demonstrates the practical relevance of this framework with practical applications ranging from drug discovery to mesh and image segmentation.

Bio:
Mustafa Hajij received his Master of Science in Computer Science and Ph.D. in Mathematics from Louisiana State University. He completed his postdoctoral training within the Departments of Computer Science at both the University of South Florida and Ohio State University. Before joining the USFCA, he was an assistant professor in the Department of Mathematics and Computer Science at Santa Clara University (SCU). Prior to SCU, he spent a year as an AI Research Scientist at KLA Corporation. He is also the founder of AltumX, a startup specializing in bringing intelligent solutions to road management. His research interests lie at the intersection of higher-order networks, topological data analysis, and geometric data processing.
Dr. Hajij was invited to present his work by Dr. Sameer Antani and his group, CHRB, LHNCBC, NLM IRP.