Dr.-Ing. Edouard Fouché
- Wissenschaftlicher Mitarbeiter (Postdoc)
- Raum: 342
- Tel.: +49 721 608-47337
- Fax: +49 721 608-47343
- edouard fouche ∂does-not-exist.kit edu
Lehrstuhl
Prof. K. BöhmKarlsruher Institut für Technologie
Am Fasanengarten 5
76131 Karlsruhe
GERMANY
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
| Titel | Datum | Typ | Bearbeiter | Zusatzfeld |
|---|---|---|---|---|
| Subspace Search in Data Streams | May 19 - Oct 19 | Master's thesis | Florian Kalinke |
|
| Anytime Tradeoff Strategies for Multiple Targets | May 19 - Nov 19 | Master's thesis | Marco Heyden |
|
| Interactive Visualization of Correlations in High-Dimensional Streams | Mar 19 - Jun 19 | Bachelor's thesis | Yimin Zhang |
|
| Statistical Generation of High-Dimensional Data Streams with Complex Dependencies | Jun 18 - Nov 18 | Bachelor's thesis | Alexander Poth |
|
| Adaptive Variational Autoencoders for Outlier Detection in Data Streams | Sep 18 - Feb 18 | Master's thesis | Florian Pieper |
|
| 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 |
|
| 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 |
|
| 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 |
| 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 |