CV

Education

• Ph.D. in Computer Science, Centrum Wiskunde & Informatica & University of Amsterdam (2025–Present)
  • Research focus: Insight Retrieval from Structured Data
  • Supervisors: Madelon Hulsebos, Maarten de Rijke
• M.Sc. in Cognitive Science, Osnabrück University, Germany (2021–2025)
  • GPA: 1.0 (equivalent to A+)
  • Focus: Machine Learning, Computational Neuroscience, Ethics of AI
  • Thesis: Emergence of language in situated environments (Grade: 1.0)
• B.Sc. in Information Systems, Osnabrück University, Germany (2018–2021)
  • GPA: 2.1
  • Thesis: Simulation environment for analyzing the spread of SARS-CoV-2 using ML agents (Grade: 1.0)

Work Experience

• PhD Student, Centrum Wiskunde & Informatica & University of Amsterdam (Mar 2025 – Present)
  • Insight extraction from structured data
  • Research pipeline design and model development
• Junior Researcher, German Research Center for AI (DFKI), Osnabrück (Mar 2022 – Mar 2025)
  • Led work package in Green-AI Hub with 5 contributors
  • Projects: In-context image classification, RAG systems, LLM evaluation
  • Promoted from Research Assistant based on prior work
• Research Assistant, Elia Bruni’s Lab, Osnabrück University (Apr 2023 – Present)
  • Co-authored multiple papers (including one as first author)
  • Built 3D RL experiment framework using MuJoCo
• Research Assistant, Distributed Systems Lab, Osnabrück University (Jun 2021 – Mar 2023)
  • First-author peer-reviewed paper
  • Focus: Distributed systems and scientific data analysis
• Freelance AI Developer (Remote, Jun 2021 – Mar 2023)
  • Projects: RAG, synthetic data for embeddings, NLP tools
  • Soft skills: Client relations, project coordination

Skills

• Programming: Python (PyTorch, TensorFlow, Pandas), JavaScript/TypeScript, Tailwind CSS, SQL
• ML/NLP: LLMs, RAG, RL, SNNs, Vector Databases
• Tools: Git, Bash/Zsh, Linux, LaTeX (Overleaf, R Markdown)

Publications

PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers

Schiesser, L., Wolff, C., Haas, S., & Pukrop, S. (2025). "PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers." arXiv preprint arXiv:2506.14842.

How well do LLMs reason over tabular data, really?

Wolff, C., & Hulsebos, M. (2025). "How well do LLMs reason over tabular data, really?" 4th Table Representation Workshop - ACL 2025.

Bidirectional Emergent Language in Situated Environments

Wolff, C., Mayer, J., Bruni, E., & Ohmer, X. (2024). "Bidirectional Emergent Language in Situated Environments." arXiv preprint arXiv:2408.14649.

GRASP: A Novel Benchmark for Evaluating Language Grounding and Situated Physics Understanding in Multimodal Language Models

Jassim, S., Holubar, M., Richter, A., Wolff, C., Ohmer, X., & Bruni, E. (2024). "GRASP: A Novel Benchmark for Evaluating Language Grounding and Situated Physics Understanding in Multimodal Language Models." Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, 6297-6305.

A Review of Nine Physics Engines for Reinforcement Learning Research

Kaup, M., Wolff, C., Hwang, H., Mayer, J., & Bruni, E. (2024). "A Review of Nine Physics Engines for Reinforcement Learning Research." arXiv preprint arXiv:2407.08590.

A New Approach on Estimating Germany’s Mobile Broadband Coverage based on Crowdsourced Data

Wolff, C., Tessmer, A., & Aschenbruck, N. (2023). "A New Approach on Estimating Germany's Mobile Broadband Coverage based on Crowdsourced Data." Mobile Communication-Technologies and Applications; 27th ITG-Symposium, 31-36.

Talks

Can We Create Green AI? - Podcast Interview

December 19, 2024

Podcast Interview at Kaleidoscience: Conversations on Cognitive Science, Osnabrück, Germany

Teaching

Study Project: LLMs for Science

Emergent Behavior in Multi-Agent Systems (EBIMAS)

Service and Leadership

• Master’s application selection committee member (2023–2025)
• Led research project groups (20+ students) in EBIMAS
• Supervised 4 bachelor theses
• Led work package at DFKI with interdisciplinary collaboration