gaedke®.ai About
About

Before you trust an outside view, check the record behind it.

Here is mine: nearly three decades of research, industry work, and leadership, and where to check it.

I am Martin Gaedke. Below are the facts, the story behind them, and the sources, so you can judge for yourself whether my view is worth asking for. Request a fit check.

The record

Six facts, and where to check them.

1997
co-author of the first paper on web engineering, WWW6 conference
200+
publications, 1997 to 2026
39th
worldwide in knowledge engineering, AMiner AI 2000 list, 2020
Dean
of a computer science faculty, 2019 to 2025
Director
of a university computing centre, 2021 to 2026
6
funded research projects in my record, with EU, DFG, and BMBF funding, since 2010

The 1997 paper can be checked by its DOI; that it was the first is my own statement. The publications from 2000, the two roles, and the six funded projects are in my ORCID record. The AMiner ranking is as reported in 2020. The roles and industry projects further down are my own statements.

Where I come from

One question, asked for nearly three decades.

Prof. Dr. Martin Gaedke

How do systems, technical and human, coordinate under uncertainty without breaking? I studied computer science and earned my doctorate at the University of Karlsruhe (today KIT). In 1997, when the web was still engineered by hand, I co-authored the first paper on web engineering, at the WWW6 conference in Santa Clara. In the same years I led industry projects in Karlsruhe with Daimler-Benz, Hewlett-Packard, Microsoft, and Microsoft Research. That work led to component-based and model-driven methods, to mashups that let non-programmers build their own tools, and to linked data and knowledge graphs that connect what organisations know.

Since 2007 I have been a full professor of computer science. Research alone would have kept this abstract. As dean of a computer science faculty from 2019 to 2025, and as director of a university computing centre from 2021 to 2026 and a member of the university's CIO board, I carried responsibility for people, infrastructure, and IT strategy under real constraints. That is where I learned what an organisation can actually absorb.

Today the same question has a new subject: AI agents that act on behalf of people, and the rules they have to act within. I am a founder of the International AIQT Foundation, a platform for exchange on artificial intelligence and quantum technology. And I try what I recommend on myself. My own company is run by one person and a fleet of AI agents, and its operating rules are public.

Roles and service
Research

What I work on, and where to read it.

NowAI agents and governance How AI agents can act within an organisation's rules, for example “Towards Governance-Aware Local and Hybrid AI Agents for Web Applications” (2026).
NowAI for scientific knowledge Methods that use language models to build and refine scientific knowledge graphs, for example “Deep Semantic Linking of Scientific Knowledge: An Agentic AI Framework for Knowledge Graph Construction” (2026).
OngoingConversational interfaces and user experience How chatbots and web interfaces are designed, measured, and sometimes misused, for example “In Search of Dark Patterns in Chatbots” (2024).
OngoingTrust, identity, and the decentralised web Who can be trusted with data on the web, from WebID to Solid, for example “Trusting Decentralized Web Data in a Solid-Based Social Network” (2024).
Since the 2010sLinked data and research data management Connecting and describing data across institutions so that it stays findable and usable, for example “ResearchFlow: An End-User Development Approach to Research Data Management Workflow Composition” (2026).
Since 1997Web engineering foundations Component-based and model-driven development of web applications, for example “Towards DSL-based Web Engineering” (2006).

The full record: orcid.org/0000-0002-6729-2912

Projects

Funded research and industry projects.

All six are listed as funded work in my ORCID record.

European Commission · 2023 to 2026ENFIELD: European Lighthouse to Manifest Trustworthy and Green AI A European lighthouse project on trustworthy and green AI.
DFG · from 2023Non-invasive interdisciplinary research data management in federated organisational environments Managing research data across federated organisations without disrupting how they work.
DFG · from 2020Systematic, interdisciplinary, and sustainable research data management An information infrastructure for research data in transdisciplinary research environments.
BMBF · 2015 to 2018LEDS: Linked Enterprise Data Services A subproject on putting quality-optimised, semi-structured enterprise data to use through linked data services.
DFG · 2012 to 2016CrossWorlds: Connecting Virtual and Real Social Worlds A research training group on how virtual and real social worlds connect.
European Commission · 2010 to 2013Open Mashup Enterprise service platform for linked data in the telecom domain An enterprise mashup platform for linked data.

The thread: each concerns making data, systems, and people work together.

Industry projects · as a researcher in Karlsruhe · 1997 to 2001
Hewlett-PackardeVictor Lead and architect of a large-scale, worldwide procurement portal.
Daimler-BenzMobilBot A web platform for mobile travel services and intelligent travel assistance.

Also 1997 to 2001: industry projects with Microsoft and Microsoft Research.

Research and innovation partners

Collaboration, not only engagements.

A second kind of message is just as welcome. Teams building a collaborative research or innovation project write to ask whether the topic fits, what an expert partner would contribute, and whether a joint idea is worth developing.

I take part in collaborative projects on both sides of the transfer gap: as a research partner in publicly funded consortia, and as an expert partner in applied, industry-oriented work. If your project touches agentic systems, AI governance, or the transfer of AI research into practice, that is exactly the overlap. Consortium building runs on its own clock, so early beats complete: a call topic, a draft concept, or a gap in the partner map is enough to start the conversation.

Say what the project is about, what stage it is at, and what is still missing. You get an honest answer about fit, including a no when the fit is not there.

Write to martin@gaedke.ai, or see how a first message is answered.

Contact

Request a fit check.

Write to me directly

Tell me what you are deciding, or what your project needs, and by when. You get a personal answer from me, as a rule within two working days.

Some browsers have no mail application configured and will not open a mail window, so the address is here in full to copy or type.
Also on LinkedIn: in/gaedke

My external work is focused on scientific services, scientific review, scientific writing, and knowledge transfer. This includes expert assessments, research-based recommendations, and transfer-oriented collaboration at the interface of science and practice. This website does not offer legal advice, tax advice, or unrestricted management consulting. Expert and review mandates for public bodies are carried out independently of the engagements described here, and neither is ever used to obtain the other. The services offered here are carried out independently of my university role and without the use of university resources. Research partnerships in publicly funded consortia are arranged in whichever role the project requires, and that is settled before any commitment.