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|Profile Image{: style="margin:0em; padding:0em; width:10em"}| | Steffen Illium
AI Consultant &
Data Scientist
|

Grab my CV here{: .btn .btn--success data-umami-event="CV Download"}

My career has been driven by a passion for turning data into actionable insights. This journey began with a BSc in Geography from JGU Mainz and an MSc in Geo-Informatics from the University of Augsburg, culminating in a PhD in Computer Science (summa cum laude) from LMU Munich. During my doctoral studies and subsequent role as a research assistant at LMU (2018-2023), I focused on developing machine learning models for sequential data, advancing self-learning systems, and contributing to foundational research in neural network applications.

A significant part of my research involved collaborating with industry partners. Key projects include "ErLoWa," focused on leak detection in water networks, and "AI-Fusion," which dealt with detecting emergent dysfunctions in multi-agent reinforcement learning (MA-RL). These experiences provided me with extensive expertise in audio signal processing, deep learning for sequence and image analysis, and MARL, particularly concerning safety and emergence in industrial contexts. This blend of theoretical research and practical application is detailed in my publications and research pages.

Beyond my core research, I have actively contributed to teaching and academic service. My experience includes lecturing, supervising practical courses (such as iOS and Android development), managing seminars (IMAPS), leading Python crash courses, and mentoring numerous students through their Bachelor's (20) and Master's (9) theses. You can find more details on my teaching page.

I have also embraced leadership and organizational responsibilities within the academic community. I served as the lead organizer for the OpenMunich conference from 2018 to 2019 and headed the editorial team for "DIGITALE WELT Magazin" from 2018 to 2023. These roles broadened my experience in project management, communication, and community building.


Research Profiles


Scholar arXiv R-Gate ORCiD LMU Semantic

Core Competencies & Technical Skills

Roles & Expertise:
Teacher Researcher Data Scientist Machine Learning Expert AI Consultant System Administrator Project Management Editor in Chief

Concepts & Methodologies:
Machine Learning Deep Learning Data Augmentation Classification Segmentation Anomaly Detection Out-of-Distribution Detection Reinforcement Learning Multi-Agent RL Emergence Industrial Safety (AI) Geoinformatics

Programming Languages:
Python LaTeX Kotlin PHP Shell Script HTML5 CSS3 Markdown JavaScript

Libraries & Frameworks (Python Focus):
PyTorch NumPy Pandas Scikit-learn FastAPI Matplotlib Plotly Langchain MLFlow GDAL/OGR scikit-spatial

Systems & DevOps:
Linux Docker Kubernetes Git Nginx Traefik Proxy WireGuard ZFS

Databases:
SQL (General) MongoDB

Tools & Software:
VS Code IntelliJ IDEA Microsoft Office Obsidian


Thank you for your interest in my profile.