collaborate

Collaboration entry point for industry, public-sector, and academic partners.

Collaboration

This page is the entry point for collaboration with the research group of Prof. Dr.-Ing. Michael Färber (ScaDS.AI / TU Dresden).

Our core topics include trustworthy AI, LLMs / chatbots / question answering, retrieval-augmented generation (RAG) and evidence-based generation, knowledge graphs, and graph machine learning.

Collaboration formats (typical)

  • Publicly funded projects (preferred when possible): joint proposals (e.g., DFG / BMBF / EU-style calls), with clear milestones and publishable outcomes.
  • Industry / public-sector pilots (4–12 weeks): scoped feasibility studies, benchmarking, or prototypes that de-risk a larger project.
  • Contract research / applied prototypes (3–12 months): implementation and evaluation under agreed constraints (incl. NDA/IP).
  • Student theses / student projects (co-defined topics): strong fit when the topic is well-scoped and results can be documented (often publishable).
  • Research stays / visiting researchers: short visits to collaborate on a concrete research question.

layout: page permalink: /collaborate/ title: collaborate description: Collaboration entry point for industry, public-sector, and academic partners. nav: false search: true og_image: /assets/press/Michael_Faerber_2024_700p.jpg —

Collaboration

This page is the entry point for collaboration with the research group of Prof. Dr.-Ing. Michael Färber (ScaDS.AI / TU Dresden).

Our core topics include trustworthy AI, LLMs / chatbots / question answering, retrieval-augmented generation (RAG) and evidence-based generation, knowledge graphs, and graph machine learning.

Collaboration formats (typical)

  • Publicly funded projects (preferred when possible): joint proposals (e.g., DFG / BMBF / EU-style calls), with clear milestones and publishable outcomes.
  • Industry / public-sector pilots (4–12 weeks): scoped feasibility studies, benchmarking, or prototypes that de-risk a larger project.
  • Contract research / applied prototypes (3–12 months): implementation and evaluation under agreed constraints (incl. NDA/IP).
  • Student theses / student projects (co-defined topics): strong fit when the topic is well-scoped and results can be documented (often publishable).
  • Research stays / visiting researchers: short visits to collaborate on a concrete research question.

We often start with a small, well-scoped pilot to align expectations and “test the waters” before moving to larger funding or long-term collaborations.

Typical pilot deliverables (examples):

  • a short technical report (findings + recommendation)
  • a benchmarking / evaluation of candidate methods
  • a prototype (reproducible code + minimal demo)
  • a project plan for a larger funded proposal

Publications, IP, and data (practical)

  • Publication-first by default: whenever feasible, we aim for publishable results and open artifacts (code/data) in line with academic best practice.
  • Confidentiality/IP: NDAs and review periods are possible; we clarify constraints early so projects remain feasible.
  • Student theses: as a rule, theses should be publishable; delays can be agreed for IP/patent or sensitive data, but fully non-publishable thesis topics are typically not a good fit.
  • Data access: please state early whether data is sensitive (personal data, trade secrets, security constraints) and how access can be provided (on-site, secure VM, anonymized subset, etc.).

If a collaboration is publicly announced, this should be coordinated in advance.

What to send (1-page brief)

Please send a short email including a 1-page brief with:

  • problem statement and context (what is the pain point?)
  • what success looks like (deliverables)
  • available data + constraints (privacy, access, IP)
  • desired timeline and budget range (rough is fine)
  • who will be involved on your side (roles)

Contact

For contact details, please see /contact/.
For press inquiries, see /media/ and /press-kit/.

We often start with a small, well-scoped pilot to align expectations and “test the waters” before moving to larger funding or long-term collaborations.

Typical pilot deliverables (examples):

  • a short technical report (findings + recommendation)
  • a benchmarking / evaluation of candidate methods
  • a prototype (reproducible code + minimal demo)
  • a project plan for a larger funded proposal

Publications, IP, and data (practical)

  • Publication-first by default: whenever feasible, we aim for publishable results and open artifacts (code/data) in line with academic best practice.
  • Confidentiality/IP: NDAs and review periods are possible; we clarify constraints early so projects remain feasible.
  • Student theses: as a rule, theses should be publishable; delays can be agreed for IP/patent or sensitive data, but fully non-publishable thesis topics are typically not a good fit.
  • Data access: please state early whether data is sensitive (personal data, trade secrets, security constraints) and how access can be provided (on-site, secure VM, anonymized subset, etc.).

If a collaboration is publicly announced, this should be coordinated in advance.

What to send (1-page brief)

Please send a short email including a 1-page brief with:

  • problem statement and context (what is the pain point?)
  • what success looks like (deliverables)
  • available data + constraints (privacy, access, IP)
  • desired timeline and budget range (rough is fine)
  • who will be involved on your side (roles)

Contact

For contact details, please see /contact/.
For press inquiries, see /media/ and /press-kit/. Selected funding & partners: /funding/.