Justin M. Curry

Justin M. Curry is a tenured Associate Professor in the Department of Mathematics and Statistics at the University at Albany SUNY. His research focuses on developing theoretical foundations for Topological Data Analysis (TDA) using sheaf theory and category theory. He completed his PhD at the University of Pennsylvania under Robert Ghrist and held a postdoc at Duke University. Recent activities include sabbaticals at the University of Oxford, VU Amsterdam, and the Max Planck Institute for Mathematics in the Sciences (MPI MiS).

• Education: PhD in Mathematics from University of Pennsylvania (2014)
• Visiting Associate at the Institute for Advanced Study (2009-2011)

Research interests span applied topology with emphasis on algebraic and geometric models for space communications, topological deep learning, and inverse problems in TDA. Notable collaborations include NASA's TIMAEUS project (2020-2025) and contributions to the IEEE Aerospace Conference. His work bridges pure mathematics and engineering applications, particularly in distributed space networks and topological signal processing.

Recent publications (2021–2024) explore decorated Reeb spaces, universal ℓ^p-metrics on merge trees, and topological attributed graphs for shape discrimination. He has delivered invited lectures at venues like the International Conference on Machine Learning (ICML) and the Max Planck Institute.

• Awards: NSF CRII Award (2020), NSF Grant for Enriched Topological Summaries (2019)

Advising 5 PhD students and leading the NASA-funded TIMAEUS initiative ($650k), his lab integrates categorical methods with geometric deep learning frameworks. Current work includes algebraic models for space communication protocols and sheaf-theoretic approaches to shape space construction.

Labs/Teams: Active member of the ATiA (Applied Topology and Inverse Problems) research group and collaborator with NASA's DTN (Disruption Tolerant Networking) working group.