Tiphaine Viard is an associate professor and researcher with 12 years of experience specializing in AI as a socio-technical system, graph-based machine learning, and large-scale interaction stream analysis. Based in Paris and seeking research-level opportunities in Tokyo, she combines formal theoretical work with practical applications in anomaly detection, recommender systems, and bipartite/clique detection on datasets with hundreds of millions of interactions. Her background includes postdoctoral research at RIKEN and CNAM where she applied graph neural networks and engineered scalable heuristics for NP-hard problems in real traffic data. She holds a PhD in computer science (received with high honors) and a track record of interdisciplinary collaboration across France, Japan, and industry. Notably, her work bridges formal definitions and deployed algorithms, revealing how large structural patterns in graphs can signal real-world anomalies and ethical dimensions of AI discourse.
12 years of coding experience
1 year of employment as a software developer
PhD, Computer Science, Received with high honors, PhD, Computer Science, Received with high honors at University Pierre and Marie Curie
Engineer's diploma (equivalent to MSc), Computer Science, Engineer's diploma (equivalent to MSc), Computer Science at Efrei Engineering institute
Networks, Coding Theory, Operating Systems, Entrepreneurship, Negotiation, Networks, Coding Theory, Operating Systems, Entrepreneurship, Negotiation at University of Staffordshire
Bachelor of Science, Mathematics and Computer Science, Bachelor of Science, Mathematics and Computer Science at University of Marne-la-Vallée
Contributions:35 commits, 3 PRs, 24 pushes in 4 years 3 months
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