Alonso Allende is an AI researcher at Nokia Bell Labs with eight years of industry experience and a deep academic pedigree including a Ph.D. in Physics from École Supérieure d'Électricité and postdoctoral work at UC Berkeley and INRIA. He combines theoretical expertise in game theory, random geometric graphs and spectral analysis with hands-on ML engineering, having built production RAGs, knowledge-graph–backed retrieval systems, structured output and restricted-generation pipelines, and LLM agents. His background spans telecom-focused analytics and algorithm design at Bell Labs and Safran, applying mathematics to temporal data, auctions, and network congestion problems. Comfortable moving between research and product, he codes prototypes and simulations (Java/Matlab historically) and now implements scalable generative-AI solutions for internal knowledge bases. Notably, he has repeatedly bridged multi-layer market and network models to inform practical ML systems, reflecting an unusual blend of mathematical rigor and applied system-building. Based in Paris, he focuses on Generative AI, LLMs, data analysis and game-theoretic approaches to complex systems.
8 years of coding experience
12 years of employment as a software developer
Ph.D., Physics, Ph.D., Physics at École Supérieure d'Électricité
Mathematical Engineer, Mathematical Engineering, Mathematical Engineer, Mathematical Engineering at Universidad de Chile
Contributions:98 commits, 144 pushes, 1 branch in 1 year 10 months
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