PeopleofSuperintelligence

Researcher

Joan Bruna

Joan Bruna is a professor of computer science and data science at NYU and a co-founder of its Math and Data group; his research develops mathematical foundations for machine learning. He studied mathematics and telecommunications in Spain and applied mathematics in France, earning an applied mathematics PhD in 2013. His work includes a 2012 wavelet scattering network for image classification and a 2013 graph-based extension of convolutional networks. After working as a research engineer and holding postdoctoral roles at NYU and Facebook AI Research, he joined UC Berkeley in 2015. He received a Sloan Research Fellowship in 2018 and an NSF CAREER Award in 2019, and his coauthored neural-network paper received ICLR’s Test of Time Runner-Up in 2024.

Works
184

Publication numbers from OpenAlex, as of 15 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2002–2005

    Studying mathematics and telecommunications

    He earns a mathematics degree at Polytechnic University of Catalonia in 2002, telecommunications degrees there in 2004, and an applied mathematics MSc at École Normale Supérieure in 2005.

  2. 2012

    Wavelet scattering for images

    In 2012, he and Stéphane Mallat publish a wavelet scattering network that computes translation-invariant image representations stable to deformations for classification.

  3. 2013

    A PhD and graph networks

    Before his doctorate, he works as a research engineer at an image-processing startup, developing real-time video algorithms. He completes a PhD in applied mathematics at École Polytechnique in 2013. In December 2013, he and three coauthors propose CNN architectures for graph signals using hierarchical clustering or the graph Laplacian.

  4. 2015

    Statistics professor at Berkeley

    After a postdoctoral stay at NYU’s Courant Institute and a postdoctoral fellowship at Facebook AI Research, he becomes an assistant professor in UC Berkeley’s Statistics Department in January 2015.

  5. 2018–2019

    Sloan and CAREER awards

    He wins a Sloan Research Fellowship in 2018 and an NSF CAREER Award in 2019.

  6. 2024

    An ICLR Test of Time award

    He and coauthors receive ICLR’s 2024 Test of Time Runner-Up for “Intriguing properties of neural networks.” The paper highlights how small, almost imperceptible input variations can fool neural networks and prompts work on adversarial attacks and defenses.

  7. As of October 2026

    Professor and group co-founder

    He is a professor of computer science and data science at NYU and a co-founder of its Math and Data group. His research focuses on mathematical foundations of machine learning.

Sources and credits

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  1. Joan Bruna | NYU Courant cims.nyu.edu. Checked 15 October 2026.
  2. [1203.1513] Invariant Scattering Convolution Networks arxiv.org. Checked 15 October 2026.
  3. Joan Bruna | Department of Statistics statistics.berkeley.edu. Checked 15 October 2026.
  4. [1312.6203] Spectral Networks and Locally Connected Networks on Graphs arxiv.org. Checked 15 October 2026.
  5. Colloquium Details | NYU Computer Science cs.nyu.edu. Checked 15 October 2026.
  6. Sloan Fellowship | NYU Computer Science cs.nyu.edu. Checked 15 October 2026.
  7. Achievements | NYU Computer Science cs.nyu.edu. Checked 15 October 2026.
  8. ICLR 2024 Test of Time Award blog.iclr.cc. Checked 15 October 2026.
  9. Joan Bruna cims.nyu.edu. Checked 15 October 2026.
  10. Tenure-Track Faculty | NYU Computer Science cs.nyu.edu. Checked 15 October 2026.