$ whoami
I help businesses find where AI pays off and build agentic workflows they can trust.
Düsseldorf, Germany
scrollI am a Senior AI Engineer at MULTIPLAI. My work with clients has two parts. The first is finding where AI can add value to a business. I then build agentic workflows for the strongest opportunities. The second starts from the AI and agentic tools a team already uses internally. I turn them into a structured, trustworthy MLOps workflow that the team can keep using.
Trustworthiness is also what my research was about. I did my PhD (magna cum laude) in computer science at Heinrich Heine University Düsseldorf, where I also worked as a postdoctoral researcher. My work covered reinforcement learning post-training, LLM alignment, uncertainty quantification and hallucination reduction. More recently it has moved to knowledge graph grounding and agentic systems for trustworthy AI. Over more than ten years in academia and industry, I have published at NeurIPS, ACL and EMNLP. I also wrote the open-source tooling behind that work.
Reinforcement learning and multi-agent coordination for long-horizon decision making in agentic dialogue and tool-using systems.
Reinforcement learning methods for aligning large language models using intrinsic and self-supervised reward signals, reducing reliance on external human preference data.
Reproducible, configurable and distributed training systems enabling rapid experimentation across HPC and cloud environments.
LLM-driven construction and traversal of knowledge graphs (ontology induction from dialogue and natural-language-to-SPARQL/SQL query generation), extending uncertainty-aware methods to entity linking and schema-grounded reasoning for trustworthy, hallucination-resistant enterprise AI.
Bayesian and distributional methods for uncertainty estimation, calibration and robustness, applied to trustworthy and controllable AI systems.
$ tail -n 8 ~/highlights.log
The agentic-skills marketplace carries commits and pull requests, diagnostics, research and Python quality gates. The okf-kb marketplace compiles collected sources into a wiki an agent maintains, with per-source provenance. Eleven plugins between them.
"Leveraging Low-Level Symbolic Competences for Unsupervised Grounding in Hallucination Detection": an LLM builds an SQL database from the reference material and checks each response against it, matching supervised hallucination detectors without any domain-specific training.
"Text-to-SQL Task-oriented Dialogue Ontology Construction": an LLM builds a task-oriented dialogue ontology from scratch using only its SQL capabilities and dialogue-theory concepts in the prompt.
I help clients find where AI adds value and build agentic workflows for the strongest opportunities. I also turn their internal AI use into trustworthy MLOps workflows.
"Less is More: Local Intrinsic Dimensions of Contextual Language Models". The paper uses the geometry of contextual embeddings to study LLM training dynamics and generalisation.
"Post-Training Large Language Models via Reinforcement Learning from Self-Feedback": the model's own confidence becomes the intrinsic reward, with no human feedback required.
"A Confidence-based Acquisition Model for Self-supervised Active Learning and Label Correction": confidence-driven active learning and label validation for sequential multi-output tasks.
Dissertation "Uncertainty Estimation, Management, and Utilisation in Human-Computer Dialogue" defended at Heinrich Heine University Düsseldorf.
$ git log --oneline --career
bd93f9 (HEAD -> now)
Jul 2026 → Present · Düsseldorf, Germany
ff79c6
Mar 2024 → Jun 2026 · Düsseldorf, Germany
8be9fd
Jul 2019 → Mar 2024 · Düsseldorf, Germany
50fa7b
Jun 2018 → May 2019 · Pretoria, South Africa
Configuration-driven deep learning experiment launcher
Open-source experiment launcher unifying Facebook Hydra, Hugging Face Accelerate and the UV workflow. One config launches anything from a local debug run to multi-GPU distributed training on SLURM clusters or SkyPilot-managed cloud, with no code changes between backends.
Workflow, research and code-quality plugins that share one rule: review gates before anything irreversible, and never a bypassed hook.
$ claude plugin marketplace add carelvniekerk/agentic-skills 10 plugins · 17 skills · 4 agents · 5 hooks · 1 MCP server
A knowledge base an agent maintains and you can still trust. Sources stay verbatim, the wiki is regenerated, and every claim traces back to the file it came from.
$ claude plugin marketplace add carelvniekerk/okf-kb $ uv tool install "okf-kb[all] @ git+https://github.com/carelvniekerk/okf-kb" 5 plugins · 12 skills · 1 hook · 2 MCP servers
selected work — NeurIPS · ACL · EMNLP · TACL
Renato Vukovic, Hsien-chin Lin, Carel van Niekerk, Benjamin Ruppik, Michael Heck, Shutong Feng, Nurul Lubis, Milica Gasic
Renato Vukovic, Carel van Niekerk, Michael Heck, Benjamin Ruppik, Hsien-Chin Lin, Shutong Feng, Nurul Lubis, Milica Gasic
Carel van Niekerk, Christian Geishauser, Michael Heck, Shutong Feng, Hsien-chin Lin, Nurul Lubis, Benjamin Ruppik, Renato Vukovic, Milica Gašić
Benjamin Matthias Ruppik, Julius von Rohrscheidt, Carel van Niekerk, Michael Heck, et al.
Michael Heck, Carel van Niekerk, Nurul Lubis, Christian Geishauser, Hsien-Chin Lin, Marco Moresi, Milica Ga\vsi\'c
University of Pretoria · Jan 2013–Nov 2015 · Pretoria, South Africa
University of Pretoria · Jan 2016–Nov 2016 · Pretoria, South Africa
University of Pretoria · Jan 2017–Nov 2018 · Pretoria, South Africa
Statistical learning, data analytics and visualization.
Heinrich Heine University · Jul 2019–Mar 2024 · Düsseldorf, Germany
Magna cum laude. Thesis: Uncertainty Estimation, Management, and Utilisation in Human-Computer Dialogue.