Sameh Frihat
Sameh Frihat has been a researcher in the Information Engineering department at the University of Duisburg-Essen since 2021. He holds a Doctor of Engineering (Dr.-Ing.) degree in Computer Science from the University of Duisburg-Essen, where his dissertation focused on improving biomedical literature search engines for medical professionals. His research combines Information Retrieval, Natural Language Processing, and Large Language Models to enhance clinical decision support and personalized information access in the biomedical domain. He is currently a Postdoctoral Researcher at the University of Duisburg-Essen within the WisPerMed research group.
Short CV
Sameh Frihat has been a researcher in the Information Engineering department at the University of Duisburg-Essen since 2021. He holds a Doctor of Engineering (Dr.-Ing.) degree in Computer Science from the University of Duisburg-Essen, where his dissertation focused on improving biomedical literature search engines for medical professionals. His research combines Information Retrieval, Natural Language Processing, and Large Language Models to enhance clinical decision support and personalized information access in the biomedical domain. He is currently a Postdoctoral Researcher at the University of Duisburg-Essen within the WisPerMed research group.
Research Interests
- Information Retrieval
- Retrieval-Augmented Generation (RAG)
- Natural Language Processing (NLP)
- Machine Learning and AI
- Deep Learning
- Large Language Models (LLMs)
- Software Development
Courses Assisted
- Generative AI for Information Access
- Deep Learning
- Databases
- Medical Information Systems
- Context and Personalization in Health IR
Thesis Supervision
- Master’s Thesis: Evidence-based Conversational Search in Biomedicine
- Bachelor’s Thesis: Development of a Nutri-Score App
- Bachelor’s Thesis: Enhancing Document OCR Recognition
- Bachelor’s Thesis: Distance Score-based Medical Document Readability
Publications
- S. Frihat, C.L. Beckmann, E.M. Hartmann, N. Fuhr. “Document Difficulty Aspects for Medical Practitioners: Enhancing Information Retrieval in Personalized Search Engines.” Applied Sciences 13(19), 10612 (2023).
- S. Frihat. “Context-Sensitive, Personalized Search at the Point of Care.” ACM/IEEE Joint Conference on Digital Libraries (2022).
- S. Frihat, N. Fuhr. “Supporting Evidence-Based Medicine by Finding Both Relevant and Significant Works.” arXiv preprint arXiv:2407.18383 (2024).
- S. Frihat, N. Fuhr. “Integration of Biomedical Concepts for Enhanced Medical Literature Retrieval.” International Journal of Data Science and Analytics (2025).
- S. Frihat, A. Papenmeier, N. Fuhr. “Enhancing Biomedical Literature Retrieval with Level of Evidence and Bio-Concepts: A Comparative User Study.” ACM/IEEE Joint Conference on Digital Libraries (2024).
- S. Frihat, N. Fuhr. “TREC 2021: Clinical Trials Retrieval, Duisburg-Essen University Submission.” TREC (2021).