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Department of Mathematics

Probability and Data Science Seminar

Memorial union at sunset

See below for upcoming seminars or access the seminar archive.

Organizers

Nicholas Marshall and Axel Saenz Rodriguez

Timing

The Probability and Data Science Seminar will be held on Tuesdays at 3 pm in Kidder Hall 238

Monotonicity of data along Ricci flow on surfaces

STAG 213

Speaker: Alena Erchenko

Consider a closed surface M of genus greater than or equal to 2. For negatively curved metrics on M and their corresponding geodesic flow, we can study the topological entropy, the Liouville entropy, and the mean root curvature. In 2004, Manning showed that the topological entropy strictly decreases along the normalized Ricci flow if we start with a metric of variable negative curvature and asked whether monotonicity holds for the Liouville entropy. In this talk, we answer Manning's question and show that the Liouville entropy strictly increases along the flow. This talk is based on joint work with Butt, Humbert, and Mitsutani. Read more.

Human behavior and uncertainty quantification in the context of epidemiological models

Zoom: Please email Philipp Kunde for the zoom link.

Speaker: Binod Pant

Human behavior has been attributed as one of the major reasons why models perform poorly when forecasting. The first half of this talk will focus on modeling the interplay between human behavior and disease outbreaks. In a retrospective study, we show that models incorporating human behavior change capture disease trajectories better than equivalent models without behavior change. Further, I will present a study characterizing population-level human behavior change, as inferred through survey-collected behavior data from all 50 US states during the first two years of the COVID-19 pandemic.Identifiability issues, a common problem in mathematical biology, have also been attributed to why models fail to forecast properly and struggle to correctly characterize disease transmission even in retrospective studies. Using model-generated synthetic data where ground truth is known, we investigate the inference of epidemiological quantities of interests when only fitting to detected incidence… Read more.

TBA

STAG 213

Speaker: Kurt Vinhage

Read more.