About
Alexandre Mercier is a Research Associate at the Software Engineering for Business Information Systems (sebis) chair within the Faculty of Informatics at the Technical University of Munich (TUM) since July 2024. He holds a Master's degree in Computer Science from TUM, specializing in Natural Language Processing with research focus on medical applications, dialogue systems, and text generation evaluation.
Mercier completed his Master's thesis titled 'Investigating data to text approaches to achieve diversity of generated marketing text in the music industry' in January 2024 through a collaboration with startup Connactz. His academic journey began with data science work at Würth Elektronik during Bachelor studies before specializing in NLP at TUM.
His research centers on enhancing text diversity in generated content while maintaining fluency and relevance, with specific interests in medical NLP applications, voice assistant interpretability (using SHAP values), and evaluation methodologies. He investigates techniques to overcome repetitive outputs in large language models, particularly for marketing contexts in the music industry.
Mercier's publication 'JaccDiv' (2024) establishes a metric and benchmark for quantifying inter-sample diversity in generated marketing text. This work explores input data representations and model configurations to produce non-repetitive content for digital platforms, contributing significantly to natural language generation evaluation frameworks.
He advises Master's level courses including 'Natural Language Processing - Methods and Applications' and 'Software Engineering for Business Applications', and organizes the Advanced Seminar. His research is funded through projects AssistD (a digital health assistant initiative launching March 2025) and MedTech (medical information extraction from clinical trials with MRI).
Mercier operates within the sebis research group led by Prof. Dr. Florian Matthes, contributing to NLP and digital health initiatives. The group maintains active collaborations with industry partners and medical institutions on enterprise architecture management, legal AI applications, and healthcare technology development.
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