Bruno Gonçalves is the founder at Data For Science, where he consults and teaches on building reliable machine learning and LLM systems. Trained as a physicist, with a PhD in the Physics of Complex Systems (2008), he spent more than a decade using large-scale data from Twitter, Wikipedia, mobile phones and web logs to study how people communicate, move, and spread information and disease, at Indiana University, Northeastern University, Aix-Marseille Université and NYU’s Center for Data Science. He then worked as VP of Data Science & Finance at JPMorgan Chase and as a research data scientist at TRM Labs. His research has been cited more than 17,000 times.

Research

  • Network Science

    Time-varying networks, information diffusion and collective attention in online social systems.

  • Epidemic Modeling

    GLEaM and data-driven models of how diseases spread along global mobility networks.

  • Computational Linguistics

    Dialect geography, language change and the global language network, from Twitter and Google Books.

  • Political Communication

    Polarization, astroturf detection and political abuse on Twitter: the Truthy project and OSoMe.

  • Human Mobility

    City influence, segregation and integration, urban rhythms and the statistics of human travel.

  • Web Science

    How people actually browse the Web, and why the PageRank random surfer gets it wrong.

  • Statistical Physics

    Hanoi networks, anomalous diffusion, spin glasses and hysteretic optimization.

Featured Pages

Publications

70+ journal articles, books, chapters and conference papers on networks, epidemics, language and human mobility, with full-text PDFs and abstracts.

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Curriculum Vitae

Founder at Data For Science; previously VP of Data Science & Finance at JPMorgan Chase, Moore-Sloan Data Science Fellow at NYU and faculty at Aix-Marseille Université.

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Media Coverage

350+ news stories and interviews, from Wired and Scientific American to USA Today, on epidemic forecasting, language on social media and online social networks.

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Newsletter

The Data Science Briefing: a weekly newsletter on LLMs, machine learning and data science, with 340+ issues since 2019, plus long-form tutorial series.

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Live Training

Hands-on courses on LLM engineering: evaluation, RAG, agents and LLMOps. More than 170 live sessions for O’Reilly Media and Packt since 2019.

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Consulting

Hands-on LLM consulting for engineering teams: strategy sprints, RAG and agent MVPs, production hardening and fractional AI leadership.

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