Dr.-Ing. Zeyd Boukhers

Lead of FAIR Data & Distributed Analytics Group

Fraunhofer Institute for Applied Information Technology (FIT)

Institute for Medical Informatics, University Hospital of Cologne

I believe that AI and data science should be both powerful and trustworthy. My research develops machine learning, semantic web technologies, knowledge management, and FAIR data infrastructure that work reliably across domains—from healthcare and biodiversity to scholarly data and cultural heritage. With dual appointments at Fraunhofer FIT and University Hospital of Cologne, I build systems that enable researchers in any field to harness AI, semantic interoperability, and data science responsibly, transparently, and effectively.

Publications Research Projects Research Group Contact

Research Interests

Leading the FAIR Data & Distributed Analytics Group at Fraunhofer FIT

FAIR Data

Data management, FAIR principles, data spaces

Machine Learning

Deep learning, neural networks, AI applications

NLP

Natural language processing, text mining

Data Sovereignty

Data governance, privacy, security

Research Topics

Explore my research areas - click to see related publications

Recent News

September 14, 2026

Governed Capability Evolution accepted by Information and Software Technology

Our paper "Governed Capability Evolution: Lifecycle-Time Compatibility Checking and Rollback for AI-Component-Based Systems, with Embodied Agents as Case Study" has been accepted for publication in Information and Software Technology. The work introduces a governed lifecycle framework for safely upgrading AI components through compatibility checks, staged deployment, monitoring, and rollback.

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August 30, 2026

Evolutionary Soups Accepted at EMNLP 2026

Our paper "Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment" has been accepted to the EMNLP 2026 Main Conference. The work introduces an evolutionary mixture-of-experts approach for controllable multi-objective alignment of large language models.

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July 07, 2026

New DFG-Funded Project on Synthetic Health Data

Our project "Synthetic Data as a Bridge Across Health Data Silos: Evaluating Privacy, Fidelity and Utility for Cross-Domain Patient Journey Analysis" has been approved for funding by the Deutsche Forschungsgemeinschaft (DFG) as part of its Exploration Phase. The project investigates how synthetic health data can bridge fragmented healthcare data environments while preserving privacy and supporting meaningful cross-domain patient journey analysis. The work will evaluate synthetic data along three key dimensions: privacy, fidelity, and utility, in collaboration with the Institute for Biomedical Informatics in Cologne and Berlin University of Applied Sciences.

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Recent Publications

1. 2026 • Conference Paper

   Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge

   Zeyd Boukhers , Oya Beyan Deniz , Cong Yang , Christoph Lange

   The 25th International Semantic Web Conference (ISWC 2026)

   PDF

   Boukhers, Z., Beyan Deniz, O., Yang, C., & Lange, C. (2026). Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge. The 25th International Semantic Web Conference (ISWC 2026). https://arxiv.org/abs/2605.10370

   Boukhers, Zeyd, et al."Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge." The 25th International Semantic Web Conference (ISWC 2026), 2026.

   Boukhers, Zeyd, Oya Beyan Deniz, Cong Yang, and Christoph Lange."Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge." The 25th International Semantic Web Conference (ISWC 2026) (2026).

   @inproceedings{Boukhers2026autonomous,
     title = {Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge},
     author = {Boukhers, Zeyd and
              Beyan Deniz, Oya and
              Yang, Cong and
              Lange, Christoph},
     booktitle = {The 25th International Semantic Web Conference (ISWC 2026)},
     url = {https://arxiv.org/abs/2605.10370},
     publisher = {Springer},
     year = {2026}
   }

   Scientific knowledge published on the Web generally remains passive and depends on external infrastructure for validation, conflict resolution, and confidence updates. This paper introduces Autonomous FAIR Digital Objects, extending FAIR Digital Objects with portable policy execution, event announcements, and distributed agreement mechanisms based on Semantic Web standards including RDF-star, PROV-O, SHACL, ODRL, and ActivityStreams. Evaluation on thousands of FAIR Digital Objects derived from rare-disease knowledge sources examines conflict resolution, distributed execution, and robustness under adversarial conditions.

2. 2026 • Conference Paper

   Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment

   Lingxiao Kong , Steffen Staab , Cong Yang , Oya Beyan Deniz , Zeyd Boukhers

   Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026)

   PDF

   Kong, L., Staab, S., Yang, C., Beyan Deniz, O., & Boukhers, Z. (2026). Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026). https://arxiv.org/abs/2608.29978

   Kong, Lingxiao, et al."Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), 2026.

   Kong, Lingxiao, Steffen Staab, Cong Yang, Oya Beyan Deniz, and Zeyd Boukhers."Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026) (2026).

   @inproceedings{Kong2026evolutionarysoups,
     title = {Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment},
     author = {Kong, Lingxiao and
              Staab, Steffen and
              Yang, Cong and
              Beyan Deniz, Oya and
              Boukhers, Zeyd},
     booktitle = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026)},
     url = {https://arxiv.org/abs/2608.29978},
     publisher = {Association for Computational Linguistics},
     year = {2026}
   }

   Large language models increasingly need to satisfy multiple competing objectives whose preferred trade-offs vary across users and prompts. Evolutionary Soups introduces a mixture-of-experts framework for controllable multi-objective generation in which per-layer gating networks dynamically determine expert-merging coefficients from hidden representations. The gating networks are optimized using an evolutionary algorithm with greedy hypervolume contribution. Across three tasks, the method improves Pareto-front coverage and achieves strong hypervolume, linear-utility, and Tchebyshev-utility results compared with existing controllable approaches.

3. 2026 • Conference Paper

   Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records

   Zeyd Boukhers , Lingxiao Kong , Xenophon Zabulis , Georgios Toubekis

   Proceedings of the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026)

   PDF DOI

   Boukhers, Z., Kong, L., Zabulis, X., & Toubekis, G. (2026). Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records. Proceedings of the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026). https://doi.org/10.1145/3799682.3840068

   Boukhers, Zeyd, et al."Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records." Proceedings of the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026), 2026.

   Boukhers, Zeyd, Lingxiao Kong, Xenophon Zabulis, and Georgios Toubekis."Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records." Proceedings of the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026) (2026).

   @inproceedings{Boukhers2026automated,
     title = {Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records},
     author = {Boukhers, Zeyd and
              Kong, Lingxiao and
              Zabulis, Xenophon and
              Toubekis, Georgios},
     booktitle = {Proceedings of the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026)},
     doi = {10.1145/3799682.3840068},
     url = {https://doi.org/10.1145/3799682.3840068},
     publisher = {Association for Computing Machinery},
     year = {2026}
   }

   Cultural heritage records frequently represent entities such as people, places, materials, and periods as plain-text metadata values, limiting machine-actionability and cross-record navigation. This paper presents a pipeline for transforming Europeana records into a FAIR Digital Object knowledge graph structured with CIDOC-CRM. A large language model determines whether metadata values should become resolvable entity references or remain literals and links resolvable entities to controlled vocabularies such as Getty AAT, Wikidata, VIAF, and PeriodO. Evaluation on 637 archaeological records shows substantial automatic linking of previously unenriched metadata and cross-lingual entity consolidation.

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Upcoming Events & Talks

Oct

25

2026

Talk

ISWC 2026 - Presenting Autonomous FAIR Digital Objects

The Nicolaus Hotel

Presenting our paper 'Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge' at the 25th International Semantic Web Conference (ISWC 2026), introducing an operational framework for FAIR Digital Objects that can autonomously validate evidence, apply policies, communicate updates, and reconcile conflicting knowledge.

TBA Bari, Italy

Event Details

Nov

03

2026

Project Meeting

ARGUS Final Project Meeting and Final Conference

Divani Palace Acropolis

Participating in the final ARGUS project meeting from 3-5 November 2026, concluding the Horizon Europe project on non-destructive, scalable and smart monitoring of remote cultural heritage. The internal project meeting will be followed by the ARGUS Final Conference on 4-5 November, presenting the project's results on remote sensing, sensor networks, AI, digital twins, data integration, risk assessment, and preventive conservation.

TBA Athens, Greece

Event Details

Nov

07

2026

Talk

CIKM 2026 - Presenting FAIR Digital Object Knowledge Graphs for Cultural Heritage

Auditorium Parco della Musica

Presenting our short paper 'Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records' at CIKM 2026. The work investigates how flat Europeana cultural heritage metadata can be transformed into machine-actionable FAIR Digital Object knowledge graphs using CIDOC-CRM, persistent identifiers, controlled vocabularies, and large language models.

TBA Rome, Italy

Event Details

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