Team

I joined Fraunhofer SCAI in October 2019 as a master’s student and I am currently doing my PhD. My current area of research is the use of machine learning methods for predicting disease progression in neurodegenerative diseases.
 

Projects: Real4Reg

I’m a Computer Scientist that joined SCAI in late 2017. My main research focus is the development of applications for exploration, evaluation and visualization of data in the biomedical domain.

Projects: Psych-STRATA, NFDI4Health
 

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I joined SCAI in September 2025 with a background in biomedical engineering and neuroscience. I am now doing a PhD as a Marie Skłodowska-Curie Actions (EU) doctoral researcher in the AIPD network. My research focuses on the use of Neural Differential Equations-based models to generate patient-specific counterfactual scenarios (ie, a digital twin) of Parkinson's Disease.

Projects: AIPD

With a background in computer science, I am now doing my PhD exploring applications of machine learning in the biomedical domain. My current project is the development of a model to recommend options of non-pharmaceutical intervention in pandemic situations.
 

Projects: COMMUTE

Coming from neurobiology, I am now using data science and machine learning to tackle biomedical problems. My current project involves drug repositioning using deep learning methods.

Projects: ADIS
 

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I am a quantitative biologist and joined Fraunhofer SCAI in 2020 as a PhD. student. My research focuses on the generation and application of pre-trained language models for German text data from the clinical domain.

Projects: Real4Reg

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I'm a senior data scientist/project manager, passionate about pursuing healthcare and life science scientific challenges that improve the understanding of human biology and diseases. My research focuses on developing AI methods to extract relevant biomedical interactions/relationships from unstructured data (e.g., scientific literature, clinical notes, and protein sequences).

Projects: IDERHA, industry project

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I joined the group as a post-doctoral researcher in 2024, driven by a passion for applying AI methods in healthcare to advance our understanding of human biology and disease. My current research focuses on developing AI models for individualized predictions and disease prognoses, aiming to enhance decision support and personalized patient care.
 

Projects: CERTAINTY

I am a computer scientist by formal training; broadly, my interests lie in recognizing and deciphering patterns in the sequence and structure of proteins, small molecules and interactions between them. My research at SCAI focuses on the development of deep learning methods for solving problems in the area of targeted protein degradation.

I'm a physicist and joined Fraunhofer in 2022 as a PhD student. My current research interest lies in combining dynamic and mechanistic models (e.g. ODEs) with methods from machine learning to predict, analyze and model pandemics such as COVID-19.
 

Projects: PREDICTOM
 

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I joined Fraunhofer SCAI in 2019, where I completed my master’s thesis and PhD studies in biomedical data science. As a postdoctoral researcher, I focus on data integration, patient stratification, predictive modeling, and federated learning in healthcare. In the EU project CERTAINTY, I develop AI models to support individualized treatment decisions and advance precision medicine.
 

Projects: CERTAINTY

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I am a mathematician and joined Fraunhofer SCAI in 2024 as a PhD student. My research focuses on developing generative AI models for the personalized prediction and simulation of patient trajectories as part of a digital twin.
 

Projects: CERTAINTY

I joined Fraunhofer SCAI in October 2025 as a PhD student. My primary research focus is on enhancing the generalizability of AI models for predicting cognitive decline in patients with Parkinson's disease.

I am a biomedical engineer and joined Fraunhofer SCAI in June 2022 as a PhD student. My current research focuses on hybrid AI models to combine machine learning and pharmacological models to predict and analyze the effect of biomedical variables on patients' behavior for clinical studies.

Projects: Scientific Machine Learning, SYNTHIA
 

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As an applied mathematician, I joined SCAI in 2025 with the intention of contributing to relevant applications of AI and data science in biomedicine. The objective of my current research is to apply AI methods to support regulatory decision-making based on real-world data.
 

Projects: Real4Reg

I joined Fraunhofer SCAI in May 2025 to work on my Computer Science master's thesis. Here, I am researching the prediction of antidepressant response using combined electronic health records and genetic data by building a pipeline using combination of Neural Network for survival prediction and transformer-based model. I also did a lot of data preprocessing steps on UK BioBank dataset to extract cohort and to combine it with genomic data of patients to feed into model for predictions.

Since 2023, I have been working at SCAI as a student. Currently, I am working on my master's thesis, which aims to estimate the causal effects of lifestyle variables on the risk of developing Parkinson's disease using modern machine learning algorithms.

I joined Fraunhofer SCAI in October 2022 for my computer science bachelor thesis, here I fine-tuned a BERT model using structured EHR data to predict Parkinson's disease. After completing my bachelor thesis, I continued working on the project. Currently, I’m pursuing a Master's degree in Computer Science at the University of Bonn.

I joined Fraunhofer SCAI in March 2025 for my applied mathematics master thesis. Here, I develop and apply modern generative AI methods to emulate clinical studies.

I joined Fraunhofer SCAI in October 2025 to work on my applied mathematics master’s thesis. My work focuses on developing and applying a reinforcement learning approach to optimize personalized dosing strategies.