HSM Early Career Colloquium: Eugenia Franco, Pascal Steinke, Florine HartwigHSM Early Career Colloquium

Wednesday Jun 17, 2026, 3:15 PM → 4:30 PM Europe/Berlin

Endenicher Allee 60/1-016 - Lipschitzsaal (Mathezentrum)

Short research presentations by HSM Postdocs and PhD students. All are welcome to attend!

There will be tea and coffe from 3pm (15:00) in the Plücker Room.

 

Eugenia Franco

Title: Kinetic proofreading systems for immune recognition processes

Kinetic proofreading systems were proposed by Hopfield and Ninio in the 70’s in order to explain the ability of receptors to distinguish between different ligands with a low error rate. This property is called specificity in the biochemical literature. In this talk, I will describe the main properties of kinetic proofreading models. In particular I will focus on understanding the relation between the specificity of the system and the amount of energy that the system consumes. 

This work has been done in collaboration with Professor J. J. L. Velazquez.

Pascal Steinke

Title: Second-Order Gamma-limit for the Cahn-Hilliard Functional

In this short talk, we are going to discuss a higher-order Gamma-convergence result for the Cahn-Hilliard functional which describes the separation of fluids. After a short introduction to the general framework of Gamma-convergence, we are going to discuss our main result about the second-order Gamma-limit in the case of Dirichlet boundary data with subquadratic growth at the wells.

Florine Hartwig

Title: Geodesic Calculus on Implicitly Defined Latent Manifolds

Autoencoders map high-dimensional data onto low-dimensional latent manifolds. Those low-dimensional representations of data can be studied from a geometric perspective. 
We propose to describe these latent manifolds as implicit submanifolds of an ambient latent space. Based on this, we develop tools for a discrete Riemannian calculus approximating classical geometric operators. 
To obtain a suitable implicit representation, we propose to learn an approximate projection onto the latent manifold by minimizing a denoising objective. This approach is independent of the underlying autoencoder and supports the use of different Riemannian geometries on the latent manifolds. The framework in particular enables the computation of geodesic paths connecting given end points and shooting geodesics via the Riemannian exponential maps on latent manifolds.