Research Interests

Artificial intelligence (AI) and machine learning influence every aspect of our modern world. In my opinion, the responsibility of research is to ensure close interaction and collaboration between humans and AI algorithms. In my research, I investigate this human-AI-interaction from a socio-technical perspective, mostly in healthcare settings. Especially in healthcare, one necessity is human involvement in AI development, e.g. through knowledge inclusion in ML models, user-centered designs and collaborative ML.

Therefore, my main research interests manifest in

Knowledge-Guided Machine Learning
Health Information Systems
Large Language Models
Federated Learning

If you are looking for a final thesis, write me an e-mail or have a look at the list of theses here.

Projekte
Title	Project Group	Emblem
FLAIROP: Federated Learning for Robotic Picking	Ali Sunyaev, Scott Thiebes, Sascha Rank, Florian Leiser
NephroCAGE: Nephrology Disease Cooperation between Canada and Germany for Applied AI	Ali Sunyaev, Scott Thiebes, Konstantin Pandl, Florian Leiser

Publikationsliste

2024

Journal Articles

Explainable artificial intelligence for omics data: a systematic mapping study
Toussaint, P. A.; Leiser, F.; Thiebes, S.; Schlesner, M.; Brors, B.; Sunyaev, A.
2024. Briefings in Bioinformatics, 25 (1), 1–16. doi:10.1093/bib/bbad453

Conference Papers

Knowledge-Guided Learning of Temporal Dynamics and its Application to Gas Turbines
Bielski, P.; Eismont, A.; Bach, J.; Leiser, F.; Kottonau, D.; Böhm, K.
2024. 15th ACM International Conference on Future and Sustainable Energy Systems, Singapur, 4th-7th June 2024, 279–290, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661967

HILL: A Hallucination Identifier for Large Language Models
Leiser, F.; Eckhardt, S.; Leuthe, V.; Knaeble, M.; Maedche, A.; Schwabe, G.; Sunyaev, A.
2024. CHI ’24: Proceedings of the CHI Conference on Human Factors in Computing Systems. Ed.: F. Mueller, Art.-Nr.: 482, Association for Computing Machinery (ACM). doi:10.1145/3613904.3642428

Informed machine learning for cardiomegaly detection in chest X-rays: a comparative study
Hasse, F.; Leiser, F.; Sunyaev, A.
2024. Proceedings of the 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), Institute of Electrical and Electronics Engineers (IEEE)

How Experts Rely on Intuition in Medical Image Annotation – A Study Proposal
Leiser, F.; Warsinsky, S. L.; Schmidt-Kraepelin, M.; Thiebes, S.; Sunyaev, A.
2024. Proceedings NeuroIS Retreat 2023 Vienna, Austria | May 30 - June 1. Ed.: F. Davis Information Systems and Neuroscience – NeuroIS Retreat 2023, Vienna, Austria. Ed.: F. Davis, 253–261, Springer. doi:10.1007/978-3-031-58396-4_22

2023

Journal Articles

NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study
Schapranow, M.-P.; Bayat, M.; Rasheed, A.; Naik, M.; Graf, V.; Schmidt, D.; Budde, K.; Cardinal, H.; Sapir-Pichhadze, R.; Fenninger, F.; Sherwood, K.; Keown, P.; Günther, O. P.; Pandl, K. D.; Leiser, F.; Thiebes, S.; Sunyaev, A.; Niemann, M.; Schimanski, A.; Klein, T.
2023. JMIR Research Protocols, 12, Art.-Nr.: e48892. doi:10.2196/48892

Medical informed machine learning: A scoping review and future research directions
Leiser, F.; Rank, S.; Schmidt-Kraepelin, M.; Thiebes, S.; Sunyaev, A.
2023. Artificial Intelligence in Medicine, 145, Art.-Nr.: 102676. doi:10.1016/j.artmed.2023.102676

Conference Papers

Applying Random Forests in Federated Learning: A Synthesis of Aggregation Techniques
Bodynek, M.; Leiser, F.; Thiebes, S.; Sunyaev, A.
2023. Wirtschaftsinformatik 2023 Proceedings, AIS eLibrary (AISeL)

From ChatGPT to FactGPT: A Participatory Design Study to Mitigate the Effects of Large Language Model Hallucinations on Users
Leiser, F.; Eckhardt, S.; Knaeble, M.; Mädche, A.; Schwabe, G.; Sunyaev, A.
2023. Mensch und Computer 2023, 81–90, Association for Computing Machinery (ACM)

Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach
Leiser, F.; Warsinsky, S.; Daum, M.; Schmidt-Kraepelin, M.; Thiebes, S.; Wagner, M.; Sunyaev, A.
2023. Proceedings of the 56th Hawaii International Conference on System Sciences (HICSS 2023). Ed.: T.X. Bui, 2850–2859

2021

Conference Papers

What Your Radiologist Might be Missing: Using Machine Learning to Identify Mislabeled Instances of X-ray Images
Rädsch, T.; Eckhardt, S.; Leiser, F.; Pandl, K. D.; Thiebes, S.; Sunyaev, A.
2021. Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS)

CV

Florian Leiser is a Ph.D. student and research associate at the Critical Information Infrastructures Research Group.

Education

Since 09/2021: Ph.D. student at Critical Information Infrastructures Research Group at Karlsruhe Institute of Technology, Germany
10/2019 - 07/2021: Master of Science in Information Systems, Karlsruhe Institute of Technology, Germany
10/2018 - 10/2019: Student in Information Engineering and Management (Master of Science), Karlsruhe Institute of Technology (discontinued)
10/2014 - 06/2018: Bachelor of Science in Information Engineering and Management, Karlsruhe Institute of Technology, Germany

Working Experience

Since 09/2021: Research Associate, Critical Information Infrastructures Research Group, Karlsruhe Institute of Technology, Germany
03/2019 - 02/2020: Student Assistant at CAS Software AG, Karlsruhe, Germany
10/2017 - 03/2018: Internship IT-audit and Data Science at Ernst & Young GmbH, Frankfurt, Germany
10/2016 - 02/2017: Student Assistant, Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
04/2016 - 09/2016: Student Assistant, Institute of Information Systems and Marketing, Karlsruhe Institute of Technology, Germany