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Laurent Labatut is an Associate Professor (Maître de conférences HDR) in Computer Science at Sorbonne Université in Paris, France, and a researcher at the LIP6 (Laboratoire d'Informatique de Paris 6). His research primarily focuses on Artificial Intelligence, Machine Learning, Complex Systems, Multi-Agent Systems, and Data Science, with a particular interest in graph analysis, community detection, and the ethical implications of AI. He is actively involved in teaching various computer science and AI courses at both undergraduate and postgraduate levels, and supervises PhD and Master's students. His work often involves developing algorithms and models to analyze and understand complex data structures and their dynamics.
Laurent LABATUT's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Holds a tenured academic position with Habilitation à Diriger des Recherches (HDR), qualifying him to supervise doctoral theses and lead research projects at one of France's most prestigious universities.
Conducts cutting-edge research as a member of LIP6, a leading computer science laboratory in France, contributing to advancements in AI and complex systems.
Authored and co-authored numerous scientific papers published in reputable international journals and conference proceedings, showcasing significant contributions to his fields of expertise.
Successfully supervised and mentored numerous Master's and PhD students, guiding their research and contributing to the development of new talent in AI and computer science.
Contributed to the development and application of novel algorithms for graph analysis, community detection, and machine learning, addressing complex real-world problems.
HEC Paris
INSEAD
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Tafalgie Therapeutics is a French preclinical-stage biopharmaceutical company focused on developing innovative treatments for pain. They are particularly targeting neuropathic pain by developing first-in-class therapies that modulate a novel pharmacological target. Their approach aims to provide relief for patients suffering from chronic pain conditions where current treatments are often inadequate or have significant side effects.
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