CV

Education

• Ph.D. in Computer Science, Technische Universität Berlin / BIFOLD, 2025 – present
  • Supervisors: Prof. Dr.-Ing. Sebastian Schelter (TU Berlin) and Prof. Dr. Maarten de Rijke (UvA)
  • Topic: Machine Unlearning for Recommender Systems
• M.Sc. in Computer Science, Freie Universität Berlin, 2021 – 2024
  • Thesis: Neural Network Post-Filters for Video Coding (in cooperation with Fraunhofer HHI)
• B.Sc. in Computer Science (grade 1.4), Freie Universität Berlin, 2018 – 2021
• Abitur (grade 1.7), Werner-von-Siemens-Gymnasium Berlin, 2012 – 2018
  • Advanced courses: Computer Science, Mathematics

Work Experience

• Feb 2025 – present: PhD Student
  • BIFOLD – Berlin Institute for the Foundations of Learning and Data / TU Berlin, Berlin, Germany
  • Research on Machine Unlearning for Recommender Systems
  • Supervisors: Sebastian Schelter and Maarten de Rijke
• Dec 2022 – Dec 2024: Student Assistant
  • Fraunhofer Heinrich Hertz Institute (HHI), Berlin, Germany
  • Work on neural network coding for video compression
  • Wrote master’s thesis: Neural Network Post-Filters for Video Coding
• Aug 2020 – Oct 2020: Web Development Intern
  • writeaguide, Berlin, Germany
  • Fullstack web development internship

Skills

• Machine Learning & Deep Learning
  • PyTorch, scikit-learn
• Recommender Systems & Machine Unlearning
• Video Coding & Neural Network Post-Processing
• Programming: Python, C, C++
• Web Development: HTML, CSS, JavaScript (Fullstack)

Languages

• German (Native)
• English (Professional working proficiency)
• Spanish (Limited working proficiency)

Academic Service

Journals

• ACM Transactions on Information Systems (TOIS)
• IEEE Transactions on Knowledge and Data Engineering (TKDE)

Conferences

• SIGIR 2026 (Resources Track)

Publications

ERASE - A Real-World Aligned Benchmark for Unlearning in Recommender Systems

Pierre Lubitzsch, Maarten de Rijke, Sebastian Schelter. (2026). "ERASE - A Real-World Aligned Benchmark for Unlearning in Recommender Systems." In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '26), pp. 3310–3318.

Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems

Pierre Lubitzsch, Olga Ovcharenko, Hao Chen, Maarten de Rijke, Sebastian Schelter. (2025). "Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems." FAccTRec@RecSys 2025

Talks

Conference Proceeding talk 3 on Relevant Topic in Your Field

March 01, 2014

Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA, USA

Talk 2 on Relevant Topic in Your Field

February 01, 2014

Talk at London School of Testing, London, UK

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley, CA, USA

Talk 1 on Relevant Topic in Your Field

March 01, 2012

Talk at UC San Francisco, Department of Testing, San Francisco, CA, USA

Teaching

Teaching experience 2

Teaching experience 1

Projects

• Classification of reflective sentences (Apr–Jul 2022)
  • NLP project within the PetraKIP research project at FU Berlin
  • Annotation and classification of sentences according to the cognitive Gibbs cycle using machine learning
• Digit recognition neural net (Dec 2019)
  • Neural network for digit classification trained on MNIST (~97.5% accuracy), written in Python
• Joodle Dump (Mar 2019)
  • Clone of Doodle Jump written in C using the SDL2 graphics library (group project, 6 members)
• Mandelbrot Set (Jul 2018)
  • Visualization of the Mandelbrot set in C++ using the SFML graphics library
• Pong (Nov–Dec 2017)
  • Clone of Pong written in Python