Summary

Hello, I am a Postdoctoral Researcher in Data Mining at the Karlsruhe Institute of Technology (KIT).

My dissertation, "Estimating Dependency, Monitoring, and Knowledge Discovery in High-Dimensional Data Streams" (Advisor: Prof. Klemens Böhm), defended on July 2020, obtained the highest distinction (Summa Cum Laude). I hold a Master's degree in Computer Science from KIT and a Master's degree in Engineering from ESIEE Paris. I have advised 10+ students for their Master/Bachelor's theses and conducted multiple projects with major industry actors (such as Daimler, BMW, IBM, ...). Also, I am starting an MBA at the Quantic School of Business and Technology.

My research focuses on:

Unsupervised Learning in High-Dimensional Data Streams
Correlation Analysis
Bandit Algorithms
Outlier Detection / Clustering

You may find more information about me here:

Personal Website: https://edouardfouche.com
Publications: Google Scholar
Social Network: LinkedIn

Advised Theses
Titel	Datum	Typ	Bearbeiter	Zusatzfeld
Subspace Search in Data Streams	May 19 - Oct 19	Master's thesis	Florian Kalinke	GitHub
Anytime Tradeoff Strategies for Multiple Targets	May 19 - Nov 19	Master's thesis	Marco Heyden	GitHub
Interactive Visualization of Correlations in High-Dimensional Streams	Mar 19 - Jun 19	Bachelor's thesis	Yimin Zhang	GitHub
Statistical Generation of High-Dimensional Data Streams with Complex Dependencies	Jun 18 - Nov 18	Bachelor's thesis	Alexander Poth	GitHub
Adaptive Variational Autoencoders for Outlier Detection in Data Streams	Sep 18 - Feb 18	Master's thesis	Florian Pieper	GitHub
On the Interpretability of Anomaly Detection via Neural Networks	Apr 18 - Sep 18	Master's thesis	Marco Sturm	In collaboration with Daimler AG
Energy Time Series Reduction	Jan 18 - Apr 18	Bachelor's thesis	Lucas Krauß	Publication
Relevance-Driven Feature Engineering	Jul 17 - Dec 17	Master's thesis	Rosina Kazakova	In collaboration with BMW AG
High-Dimensional Neural-Based Outlier Detection	Apr 17 - Sep 17	Master's thesis	Daniel Popovic	GitHub Publication
Quality of High-Contrast Subspace Search in Data Streams with Missing Values	Feb 17 - Apr 17	Bachelor's thesis	Jonathan Bechtle	Co-advised with Georg Steinbuss

Teaching
Titel	Typ	Semester
Praktikum: Analyse großer Datenbestände	Praktikum (P)	SS 2018
Applied and Algorithmic Views on Machine Learning	Seminar (S)	SS 2017
Applied and Algorithmic Challenges in Machine Learning	Proseminar (PS)	SS 2017
Praktikum: Analyse großer Datenbestände	Praktikum (P)	SS 2017