Curriculum Vitae

PhD in Machine Learning

Machine Learning Lab, University of Freiburg, Germany

• Advisor: Prof. Dr. Frank Hutter
• Second Advisor: Prof. Dr. Marius Lindauer
• Title: Dynamic Algorithm Configuration by Reinforcement Learning

Summer School

Reinforcement Learning Summer SCOOL (RLSS'19)

Master of Science - Computer Science

University of Freiburg, Germany

• Thesis: Per Instance Algorithm Configuration
• Supervisor: Dr. Marius Lindauer
• First Examiner: Prof. Dr. Frank Hutter
• Second Examiner: Prof. Dr. Bernhard Nebel

Bachelor of Science - Computer Science

University of Freiburg, Germany

• Thesis: Data Analysis for the Selection of Recording Channels on Multielectrode-Arrays
• Supervisor: Prof. Dr. Wolfram Burgard

AutoML Conference Online Experience Chair

automl.cc

• 2024: Jointly with Gabi Kadlecová
• 2023: Jointly with Hayeon Lee, Mohammed Abdelfattah and Richard Song

COSEAL General Chair

COSEAL.net

• Jointly with Alexander Tornede (until 2023), Theresa Eimer (since 2024) and Lennart Schäpermeier

Scientific Researcher

Machine Learning Lab, University of Freiburg

Student Assistant

Machine Learning Lab, University of Freiburg

• Assisting in the implementation of research projects

Student Assistant

Chair of Computer Architecture, University of Freiburg

• Maintenance of the mobile robots for the hardware lab-course

Foundations of Deep Learning (Flipped Classroom)

Lab Course Automated Machine Learning

Seminar on Dynamic Algorithm Configuration and Optimization

Automated Machine Learning (Massive Open Online Course)

• Creation of coding exercises. Involved in setting up the MOOC

Automated Machine Learning (Flipped Classroom)

• Creation and grading of exercises & final project. Setting up online teaching through Zoom and GitHub classroom.

Automated Machine Learning

• Creation and grading of exercises & final project.

Machine Learning for Automated Algorithm Design

• Creation and grading of exercises & final project.

Hardware Lab-Course

• Assisting students with practical exercises

• ICLR, ICML, AutoML Conference, JAIR, ECAI

• JAAMAS, ICML, AutoML Conference, NeurIPS, JAIR, EWRL

• JAIR, TEVC, EWRL, NeurIPS, Journal of the ACM, AutoML Conference, ALOE@ICLR, Computational Intelligence Journal

• Journal of the ACM, NeurIPS Datasets and Benchmarks (Track 1 & Track 2), NeurIPS, AutoML@ICML, ICML

• ECAI, AutoML@ICML

• ICML, AutoML@ICML

• AAAI, AutoML@ICML

• Runner Up for the Best Paper Award at AutoML'24

• Won the Best Paper Award at GECCO'22 (GECH track)

• Best Reviewers Award (Top 10%) ICML'21

• 1st place on the meta-learning track leaderboard of the Black-Box Optimization Competition@NeurIPS'20
• 3rd place on the main track of the Black-Box Optimization Competition @NeurIPS'20