Strategy
Where AI creates real value
Finding high-impact opportunities and turning them into a credible roadmap.
- AI Strategy
- Use-case Discovery
- Governance
- Adoption
Prof. Dr. Christoph Weisser, MLitt (St Andrews), MSc (Oxford)
Bridging AI research and enterprise impact.
Business Data Science & Applied AI
Former Technical Lead Analytics & AI
Peer-reviewed research, production-grade AI, and a network of specialists helping a select group of organisations turn artificial intelligence into commercial results.
Advisory & Consulting
We take on a small number of engagements at a time and work them end-to-end, backed by a network of data scientists and software engineers.
Build
Hands-on, production-grade systems
Architectures and AI systems designed to hold up under real load.
- Generative AI
- RAG
- AI Agents
- ML Platforms
Enable
Teams that sustain the work
Upskilling people and embedding the practices that keep AI working.
- Training
- Best Practices
- MLOps
- Mentoring
AI leadership · Hands-on delivery · Executive workshops · Technical due diligence
Discuss an engagement →Academy
We provide a broad range of training programmes designed around your organisation’s specific needs, data, tools, and business challenges. Drawing on a trusted network of highly qualified scientists and subject-matter experts, we combine academic depth with practical relevance.
Python & Automation
From your first script to a working automation: Python foundations, data handling, APIs.
Business Data Science
Predictive modelling on the tabular and time-series data you already hold — features, validation, and deployment.
Generative AI & LLMs in Practice
Prompting, retrieval-augmented generation, agents, and evaluation — systems that outlast the demo.
AI for Decision-Makers
Non-technical, for executives and managers: what is possible, where value sits, how to govern it.
On-site · Remote · Hybrid
Design a programme for your team →About
I am Professor of Mathematics, in particular Business Data Science, at Hochschule Bielefeld (HSBI), and former Technical Lead Analytics & Artificial Intelligence at BASF. I started out in investment banking and quantitative finance; a doctorate in applied statistics on natural language processing and machine learning moved me into AI.
At BASF I led international AI initiatives from strategy through production deployment, and received the company’s highest performance rating in two consecutive years. Today I combine research, teaching, open-source development and selected industry collaborations to advance the practical application of AI.
My work on statistics, NLP, tabular deep learning, and the optimisation of AI systems is regularly published in leading journals and at major AI and data science conferences.
I hold Master’s degrees from Oxford and St Andrews and completed my doctorate summa cum laude in Göttingen, supported by a scholarship from the Studienstiftung des deutschen Volkes.
Summer Schools
With Dr. Knut Zoch, Research Fellow at CERN, formerly at Harvard University, I co-founded and lead Bridging AI & Society, an interdisciplinary summer school pairing the technical foundations of machine learning with the ethical, legal, and societal dimensions of AI. It has run as part of the summer academies of the Studienstiftung des deutschen Volkes since 2019.
Themes
Core ML concepts and methods, hands-on data work in Python, and AI’s societal impact.
Editions
Obertauern 2026 · Banz Abbey 2025 · Ljubljana 2024 · Koppelsberg 2021 · Cambridge (St John’s College) 2019.
Open Source
CAFE — Compound AI Factorial Evaluation
A design-of-experiments platform for evaluating RAG pipelines, AI agents, and LLM chains — factorial designs and statistical attribution, so you can tell which parts actually move the numbers.
DeepTab
Tabular deep learning behind a scikit-learn API, from Mambular to transformers. 300+ GitHub stars.
View on GitHub →Python for AI-Driven Automation
A hands-on, self-paced course from your first line of Python to a real AI-powered automation.
View on GitHub →LabelFusion
Multi-class and multi-label text classification, fusing LLM predictions with transformer classifiers through a learned fusion network.
View on GitHub →Research
I turn frontier machine learning into methods that work in production: deep learning for structured data, language, and decisions under uncertainty.
Tabular Deep Learning
Most business data is tabular. I research how deep learning applies to it.
Natural Language Processing
LLM-based classification, information extraction, and ensembles for text.
Agentic AI Systems
LLM agents that plan, use tools, and act — made reliable in production.
Explainable & Trustworthy AI
Interpretable model behaviour, so AI can be trusted in high-stakes decisions.
Predictive Analytics
Time-series models that turn historical data into forward-looking decisions.
Statistics
Distributional regression and empirical methods that quantify uncertainty.
Selected Publications
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From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning
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Probabilistic Topic Modeling with Transformer Representations
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STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module
Contact
For advisory, training, research collaboration, or media enquiries, send a short message — it reaches me directly.