Jean-Daniel Djida

Jean-Daniel Djida
Postdoctoral Researcher

  jean-daniel.djida@fau.de
  Room 03.316 | Friedrich-Alexander-Universität Erlangen-Nürnberg. FAU DCN-AvH Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship.
  +49 9131 85-67171

  My Publications at FAU-CRIS

My research sits at the crossroads of model-driven and data-driven approaches, where mathematical rigor meets real-world applications.

– Mathematical Tools for PDE Analysis: My work in this domain centers around the study and application of partial differential equations (PDEs), with a special focus on nonlinear phenomena and systems. Key areas of interest include non-linear drift-diffusion equations, control theory, mean field equations, many-particle systems, gradient flows, and the domination of semigroups. I also explore advanced techniques like entropy methods, optimal transport, functional inequalities, and the scaling behaviors of parabolic and hyperbolic systems. Additionally, I am particularly engaged in hypocoercivity and the role of diffusive models in mathematical biology.

– Mathematical Tools for Data Analysis: I am equally passionate about the development of rigorous mathematical frameworks for data analysis, especially within the contexts of inverse problems, Bayesian inference, and machine learning. My research delves into unsupervised and semi-supervised learning methodologies, with a strong emphasis on data clustering, classification, uncertainty quantification, and consistency analysis.

I believe that the relationship between mathematics and its applications is symbiotic: while mathematical analysis can significantly enhance our understanding of real-world problems, the challenges posed by these applications often lead to the discovery of novel mathematical insights. This reciprocity fuels my interest in leveraging PDE techniques to address modeling questions across a wide spectrum of scales, disciplines, and applications. By engaging in this continuous feedback loop, I aim to push the boundaries of both applied and theoretical mathematics, fostering innovation in seemingly unrelated fields.

 
 PhD Thesis: Some nonlocal operators in porous medium equations: the extension problem and regularity theory (2019)
 

Teaching

• WS 24/25: Mathematics for Engineers III
• SS 23/24: Mathematics for Engineers II
• WS 23/24: Machine Learning in Finance
 

My posts

Analysis of a local-nonlocal polymer chain model

Analysis of a local-nonlocal polymer chain model By Jean-Daniel Djida, Postdoctoral Researcher at FAU DCN-AvH What does the mathematics of ...
 

Publications

2024

2022

2021

2020

2019

2018

2017

2015

 

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