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BioQuentin Loisel is a postdoctoral researcher at the Meta-Research Innovation Center at Stanford (METRICS), where his work focuses on how artificial intelligence is transforming scientific practice and how researchers can use AI to produce better, more robust, and more equitable science. His broader agenda is to help define a hybrid model of scientific inquiry that deliberately and transparently combines human judgment and artificial intelligence.

His research sits at the intersection of artificial intelligence, epistemology of science, and research systems. He studies how AI tools reshape knowledge production across the research lifecycle, from problem formulation and data analysis to writing, peer review, and governance, and examines the epistemic, methodological, and institutional consequences of human–AI collaboration in science. His work aims to move beyond risk-focused or purely technical perspectives by developing evidence-based, researcher-centric models for integrating AI into everyday scientific practice.

Before joining Stanford, he completed a Marie Skłodowska-Curie PhD on digital technologies for co-creation, combining cognitive science, collective intelligence, and participatory research. He has co-funded and is coordinating the Artificial Intelligence working group of the Marie Curie Alumni Association (MCAA), which is a researcher-driven community of practice on AI in research. He also advises a social company, called Health Cascade, on how to integrate AI in teams to solve complex societal problems.