About Me

Steffen Illium
AI Consultant & Data Scientist

My academic and professional path reflects a deep-seated interest in transforming data into actionable insights, beginning with a foundation in Geography (BSc, JGU Mainz) and Geo-Informatics (MSc, University of Augsburg), and culminating in a PhD in Computer Science from LMU Munich (summa cum laude). During my doctoral studies and subsequent research assistant role at LMU (2018-2023), I focused on advancing machine learning models for sequential data, self-learning systems, and contributing to foundational research in neural network applications.

My research frequently involved collaborations with industry partners on projects such as “ErLoWa” (leak detection in water networks) and “AI-Fusion” (emergent dysfunction detection in MA-RL), providing extensive experience in areas like audio signal processing, deep learning for sequence and image analysis, and multi-agent reinforcement learning (MARL), particularly concerning safety and emergence in industrial contexts. This blend of theoretical research and practical application forms the basis of my publications and research activities.

Beyond core research, I have actively engaged in teaching and academic service. My experience includes lecturing, supervising practical courses (e.g., iOS, Android development), managing seminars (IMAPS), leading Python crash courses, and mentoring numerous Bachelor’s (20) and Master’s (9) theses. Details can be found on the teaching page.

Additionally, I have embraced leadership and organizational roles within the academic community. I served as the lead organizer for the OpenMunich conference (2018-2019) and headed the editorial team for the “DIGITALE WELT Magazin” (2018-2023), broadening my experience in project management, communication, and community building.