PeopleofSuperintelligence

Researcher

Danilo Jimenez Rezende

Also known as Danilo J. Rezende, Danilo Rezende

Danilo Jimenez Rezende is an AI researcher whose work developed stochastic backpropagation and normalizing flows for deep generative models. He defended a PhD thesis at EPFL in 2013 and holds degrees in physics and theoretical physics from École Polytechnique. At Google DeepMind, he spent over a decade in AI research, served as a director, led projects across the sciences, and coauthored 2017 work on memory addressing in generative models. In 2025, he joined EIT’s founding AI team as Principal Scientist, while his normalizing-flows paper received an ICML Test of Time honorable mention. Since July 2026, he leads EIT’s AI & Robotics Institute and is an Associate Professor of Artificial Intelligence at Oxford.

Now at
EIT and University of Oxford
Works
101
Citations
16,189
h-index
40
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2013

    An EPFL PhD thesis

    In 2013, he defends an EPFL PhD thesis on behavioral and computational mechanisms of multisensory integration in humans. His qualifications include a PhD in computational and cognitive neuroscience from EPFL, an MSc in theoretical physics from École Polytechnique, and a BSc in physics from École Polytechnique.

  2. 2014

    Stochastic backpropagation

    With Shakir Mohamed and Daan Wierstra, he introduces stochastic backpropagation for learning deep generative models through variational inference in 2014. The method lets these models generate data, fill missing values, and visualize high-dimensional data.

  3. 2015

    Normalizing flows for inference

    In 2015, he and Shakir Mohamed introduce normalizing flows for flexible approximate posterior distributions in variational inference. Their method transforms a simple density through invertible steps to represent more complex distributions.

  4. 2017

    Memory addressing in generative models

    In 2017, he and colleagues publish variational memory addressing for generative models, using stochastic hard attention to improve memory lookups. The method applies variational inference to retrieve memory content more precisely.

  5. 2025

    A principal scientist at EIT

    Before EIT, he spends over a decade in AI research at Google DeepMind, serves as a Director, and leads projects in nuclear physics, materials discovery, computer vision, AI agents, and medicine. In February 2025, he joins EIT’s founding team as Principal Scientist, set to lead its Artificial Intelligence Platform research. His 2015 normalizing-flows paper receives an ICML Test of Time honorable mention in 2025.

  6. Since July 2026

    Co-leading EIT’s AI institute

    In July 2026, he begins leading EIT’s AI & Robotics Institute alongside Dr Matej Macak as Executive Director & Principal Scientist. He is also Associate Professor of Artificial Intelligence in Oxford’s Departments of Statistics and Engineering Science.

Career

  1. Since 2026University of OxfordAssociate Professor of Artificial Intelligence
  2. Since 2025EITPrincipal Scientist, Executive Director & Principal Scientist
  3. 2015–2023Google
  4. 2014–2024Google DeepMindAI researcher; Director

Education

  1. 2013EPFLPhD
  2. École PolytechniqueMSc in Theoretical Physics

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Stochastic Backpropagation and Approximate Inference in Deep Generative Models2014 · 3,385 citationsWith Daan Wierstra and Shakir Mohamed
  2. Variational Inference with Normalizing Flows2015 · 1,913 citationsWith Shakir Mohamed
  3. Semi-Supervised Learning with Deep Generative Models2014 · 1,646 citationsWith Max Welling and Shakir Mohamed
  4. DRAW: A Recurrent Neural Network For Image Generation2015 · 1,280 citationsWith Alex Graves and Daan Wierstra
  5. Normalizing Flows for Probabilistic Modeling and Inference2019 · 957 citationsWith Shakir Mohamed

From OpenAlex, as of 19 October 2026.

  1. The median h-index is 53 at universities and 19 at frontier AI labsIncludes Danilo Jimenez Rezende. The median h-index is 53 at universities and 19 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  2. Of 462 people shaping AI who worked at Google, 190 work there nowIncludes Danilo Jimenez Rezende. Our estimates of where former Google and Google DeepMind people work now, including moves within Google.
  3. 14% of AI doctorate holders from 2010 to 2016 founded or led a company or lab by 10 years after graduationIncludes Danilo Jimenez Rezende. We estimate how often AI doctorate holders founded or led a company or lab by 10 years after their doctorate, and how the timing changed across cohorts.
  4. Google has the highest combined h-index among AI organizationsIncludes University of Oxford. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Behavioral and computational mechanisms of multi-sensatory integration in humans memento.epfl.ch. Checked 19 October 2026.
  2. Dr Danilo Jimenez Rezende | Ellison Institute of Technology Oxford eit.org. Checked 19 October 2026.
  3. Stochastic Backpropagation and Approximate Inference in Deep Generative Models proceedings.mlr.press. Checked 19 October 2026.
  4. Variational Inference with Normalizing Flows arxiv.org. Checked 19 October 2026.
  5. DeepMind papers at NIPS 2017 deepmind.google. Checked 19 October 2026.
  6. ICML 2025 Awards icml.cc. Checked 19 October 2026.
  7. EIT Expands Team of Field-leading Experts Spanning AI, Economics, Life Sciences, Generative Biology and Medicine eit.org. Checked 19 October 2026.
  8. Dr Danilo Jimenez Rezende and Dr Matej Macak to lead EIT’s AI & Robotics Institute eit.org. Checked 19 October 2026.