PeopleofSuperintelligence

Researcher

Francisco J. R. Ruiz

Also known as Francisco Ruiz, Francisco Jesús Rodríguez Ruiz, Francisco Jesús Rodríguez Ruíz

Francisco Ruiz is a machine-learning researcher whose work spans Bayesian inference, topic modeling, and AI-guided algorithm discovery. He completed a machine-learning doctorate at Universidad Carlos III de Madrid in 2015 and joined DeepMind in 2019 after postdoctoral work at Columbia and Cambridge. He coauthored the Embedded Topic Model and contributed to AlphaTensor, FunSearch, AlphaTensor-Quantum, and AlphaEvolve. In 2026, he coauthored research on AI-driven formal proof search and is a researcher at Google DeepMind.

Timeline

  1. 2015–2019

    PhD and postdoctoral research

    In 2015, he completes a machine-learning PhD at Universidad Carlos III de Madrid after engineering studies at the University of Seville’s ETSI and graduate study in Multimedia and Communications at Carlos III; his thesis develops Bayesian nonparametric models for time-series source separation under Fernando Pérez Cruz. After the doctorate, he spends a year as a postdoctoral researcher at Columbia and holds a Marie Skłodowska-Curie fellowship with Columbia and Cambridge. In 2019, he joins DeepMind and coauthors “Unbiased Implicit Variational Inference,” which develops an expressive variational family for Bayesian inference.

  2. 2020

    The Embedded Topic Model

    In 2020, he coauthors “Topic Modeling in Embedding Spaces,” whose Embedded Topic Model combines traditional topic models with word embeddings and learns interpretable topics from large vocabularies.

  3. 2022

    AlphaTensor finds algorithms

    In 2022, he contributes to AlphaTensor, which uses reinforcement learning to search for matrix-multiplication algorithms. It finds a 76-multiplication algorithm for a 4×5 by 5×5 product, improving on an 80-multiplication human-designed result.

  4. 2023

    FunSearch for mathematics

    In 2023, he contributes to FunSearch, which pairs a large language model with an automated evaluator to search for new solutions in mathematics and computer science. The system finds new constructions for the cap-set problem and more effective programs for bin packing.

  5. February 2024

    AlphaTensor for quantum circuits

    In February 2024, he coauthors AlphaTensor-Quantum, a deep-reinforcement-learning method for optimizing T-gate counts in quantum circuits. The system finds arithmetic algorithms for Shor’s algorithm and quantum-chemistry simulation.

  6. 2025

    AlphaEvolve for algorithm discovery

    In 2025, he contributes to AlphaEvolve, a Gemini-powered coding agent that uses large language models and automated evaluators to discover and optimize algorithms. In July 2025, he works as a researcher in Google DeepMind’s Science team.

  7. As of October 2026

    Research at Google DeepMind

    In May 2026, he coauthors research on AI-driven formal proof search; its agent uses language models with Lean verification to solve open mathematical problems. As of October 2026, he is a researcher at Google DeepMind, where he has worked since 2019.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

Sources and credits

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  1. Doctoral Thesis Defense of Francisco Jesús Rodríguez Ruíz | Signal Processing Group gts.tsc.uc3m.es. Checked 19 October 2026.
  2. Francisco Jesús Rodríguez Ruiz | Higher Technical School of Engineering etsi.us.es. Checked 19 October 2026.
  3. Unbiased Implicit Variational Inference proceedings.mlr.press. Checked 19 October 2026.
  4. Topic Modeling in Embedding Spaces - ACL Anthology aclanthology.org. Checked 19 October 2026.
  5. Discovering novel algorithms with AlphaTensor — Google DeepMind deepmind.google. Checked 19 October 2026.
  6. FunSearch: Making new discoveries in mathematical sciences using Large Language Models — Google DeepMind deepmind.google. Checked 19 October 2026.
  7. AlphaTensor for Optimizing Quantum Computations — Google DeepMind deepmind.google. Checked 19 October 2026.
  8. AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms — Google DeepMind deepmind.google. Checked 19 October 2026.
  9. Francisco Ruiz, investigador en Google DeepMind, ofrecerá una charla sobre algoritmos y IA el 6 de octubre eii.us.es. Checked 19 October 2026.
  10. [2605.22763] Advancing Mathematics Research with AI-Driven Formal Proof Search arxiv.org. Checked 19 October 2026.