Bruno Gonçalves

Founder at Data For Science · Data Scientist · Network Scientist

Learn More About My Work

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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