PeopleofSuperintelligence

Researcher

Eric Tzeng

Eric Tzeng is a computer vision researcher whose work spans visual recognition, domain adaptation and Pinterest recommendation and search systems. He coauthored DeCAF, Pinterest Related Pins and a unified visual embedding for search, then studied reinforcement learning for text-to-image diffusion models. He completed a PhD in UC Berkeley’s EECS Department in 2020, and ICML gave DeCAF its 2024 Test of Time Award. As of October 2026, he is a researcher affiliated with Pinterest, where he coauthored Pinterest Canvas for image editing and enhancement.

Now at
Pinterest
Works
36
Citations
17,086
h-index
19
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2014

    Deep visual recognition

    In 2014, he coauthors DeCAF, which tests whether features from a deep convolutional network trained for object recognition can be reused for new generic visual tasks.

  2. 2015

    Pinterest Related Pins

    He coauthors a 2015 paper on Pinterest Related Pins, an item-to-item recommendation system that combines collaborative filtering with content-based ranking.

  3. 2017

    Adversarial domain adaptation

    In 2017, he coauthors Adversarial Discriminative Domain Adaptation (ADDA), which uses adversarial learning for unsupervised domain adaptation.

  4. 2019

    A unified visual embedding

    For Pinterest search, he coauthors a 2019 multi-task deep metric-learning system that learns one image embedding for several visual-search products.

  5. 2020

    Berkeley PhD

    He completes a PhD in UC Berkeley’s EECS Department in 2020 with Trevor Darrell as advisor. His thesis studies how deep learning can build visual representations that generalize across domains.

  6. 2024

    Diffusion model reinforcement learning

    In 2024, he coauthors a Pinterest ATG paper that uses reinforcement learning to improve text-to-image diffusion models with rewards for human preference, compositionality and fairness.

  7. 2024

    DeCAF Test of Time Award

    At ICML 2024, DeCAF receives the Test of Time Award, and Tzeng is among the paper’s coauthors.

  8. As of October 2026

    Research at Pinterest

    As of October 2026, he is a researcher affiliated with Pinterest, Inc. In 2026, he coauthors Pinterest Canvas, a large-scale image-generation system for image editing and enhancement.

Career

  1. 2017–2026Pinterest

Education

  1. 2020University of California, BerkeleyPhD

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

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Pinterest. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of California, Berkeley. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of California, Berkeley. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes University of California, Berkeley. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

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

Sources and credits

Photo: We have no published photo of Eric Tzeng yet. Send us a free-licensed photo.

  1. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition proceedings.mlr.press. Checked 22 October 2026.
  2. [1511.04003] Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest arxiv.org. Checked 22 October 2026.
  3. Adversarial Discriminative Domain Adaptation — CVPR 2017 Open Access Repository openaccess.thecvf.com. Checked 22 October 2026.
  4. Learning a Unified Embedding for Visual Search at Pinterest arxiv.org. Checked 22 October 2026.
  5. Ph.D. Dissertations | EECS at UC Berkeley www2.eecs.berkeley.edu. Checked 22 October 2026.
  6. Adapting Across Domains by Aligning Representations and Images | EECS at UC Berkeley www2.eecs.berkeley.edu. Checked 22 October 2026.
  7. Large-scale Reinforcement Learning for Diffusion Models pinterest.github.io. Checked 22 October 2026.
  8. ICML Test Of Time DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition icml.cc. Checked 22 October 2026.
  9. [2603.06453] Pinterest Canvas: Large-Scale Image Generation at Pinterest arxiv.org. Checked 22 October 2026.
  10. Pinterest Canvas: Large-Scale Image Generation at Pinterest arxiv.org. Checked 22 October 2026.