Tabular Deep Learning
Most business data is tabular. I research how deep learning can be applied to it.
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
Building production-grade AI, publishing peer-reviewed research, and advising a select group of organizations on turning artificial intelligence into measurable business value.
About
I work at the intersection of cutting-edge research and real-world implementation. My focus is Artificial Intelligence and Business Data Science with measurable industrial impact — from Generative AI, tabular deep learning, and natural language processing to agentic AI systems that translate cutting-edge research into production-ready AI solutions.
Before joining academia, I served as Technical Lead Analytics & Artificial Intelligence at BASF, leading international AI initiatives from strategy through production. Today, I am Professor of Mathematics, specializing in Business Data Science at Hochschule Bielefeld (HSBI). Alongside my academic work, I advise selected organizations, contribute to open-source AI software, and publish research in leading journals and international conferences.
My goal is to help organizations translate advances in Artificial Intelligence into practical solutions that create lasting business value.
Research
My research turns frontier machine learning into methods that are practical, trustworthy, and usable in production. I work across deep learning for structured data, language, and the statistics of decision-making under uncertainty.
Natural Language Processing
LLM-based classification, information extraction, and ensemble methods for text at scale.
Agentic AI Systems
LLM agents that plan, use tools, and act autonomously — and how to make them reliable in production.
Explainable & Trustworthy AI
Making model behaviour interpretable so that AI can be trusted in high-stakes decisions.
Predictive Analytics
Time-series and predictive models that turn historical data into reliable, forward-looking decisions.
Statistics
Distributional regression and empirical methods that quantify uncertainty, not just point estimates.
Open Source
DeepTab / Mambular
A library for tabular deep learning featuring Mamba (state-space), transformer, and ResNet-style models with a scikit-learn API.
View on GitHub →Python for AI-Driven Automation
A hands-on, self-paced course that takes you from your first line of Python to shipping a real AI-powered automation.
View on GitHub →LabelFusion
Multi-class and multi-label text classification with LLMs and classical models, combined through advanced ensembling.
View on GitHub →Speaking
I speak and lecture on applied AI for academic, industry, and executive audiences — translating where the field is heading into what it means for research and business.
- The state of enterprise AI: from generative models to autonomous agents
- Building trustworthy, production-grade AI systems
- From AI strategy to measurable business value
Keynotes · Guest lectures · Executive workshops · Panels
Invite me to speak →Summer Schools
Together with Dr. Knut Zoch, Research Fellow at CERN, formerly at Harvard University, I lead Bridging AI & Society, an interdisciplinary summer school that combines the technical foundations of machine learning with the ethical, legal, and societal dimensions of artificial intelligence. Offered in collaboration with the Studienstiftung des deutschen Volkes, the programme brings together participants from diverse academic backgrounds to explore both the opportunities and challenges of AI.
Themes
Core ML concepts, methods & techniques, hands-on data work in Python, and the societal impact of AI.
Recent editions
Obertauern 2026 · Banz Abbey 2025 · Ljubljana 2024 · Koppelsberg 2021 · Cambridge (St John's College) 2019.
Advisory
Alongside my academic work, I advise a select group of organizations. I work end-to-end — from spotting the right AI opportunities to building the systems and training the teams that sustain them.
Strategy
Where AI creates real value
Identifying high-impact opportunities and turning them into a credible roadmap.
- AI Strategy
- Use-case Discovery
- Governance
- Adoption
Build
Hands-on, production-grade systems
Designing architectures and building AI systems that deliver measurable impact.
- Generative AI
- RAG
- AI Agents
- ML Platforms
Enable
Teams that sustain the work
Upskilling people and embedding the practices that keep AI working after launch.
- Training
- Best Practices
- MLOps
- Mentoring
Contact
For advisory enquiries, speaking invitations, research collaboration, or media, send a short message.