Vera Bernhard is a Data Scientist at STRIDE-Lab, the Medical Data Science group at the Department of Clinical Research. Her interdisciplinary interests led her to pursue a Master’s degree in Computational Linguistics & Language Technology and Informatics.

During her studies, she focused on applying and fine-tuning (large) language models and general machine learning methods for a diverse set of tasks, including speech recognition, medical report generation, and text classification. At the same time, she discovered her passion for making large data available and discoverable by building web apps from scratch and using human-computer interaction methods to make them intuitive and user-centred. 

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After initially joining STRIDE-Lab as a student assistant and transitioning into a data science role after graduation, Vera combines her expertise in machine learning and web development to work with biomedical text data. Currently, she develops pipelines to automate systematic reviews in the domain of psychedelic therapy for psychiatric diseases. Therefore, she applies language models to classify and extract relevant information from clinical study publications, making the insights accessible through an interactive web interface. 

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Looking ahead, Vera aims to continue translating clinical needs into technical solutions, bringing together perspectives from different fields of research and making large-scale biomedical data more accessible. She is especially looking forward to moving from meta-science to working directly with clinical data. 

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“Bring medical and technical voices together early: without medical perspective, you  might solve the wrong problem; without technical perspective, you might  define one you can’t solve.”