Mario Lucic
Also known as Mario Lučić
Mario Lucic is a machine learning researcher whose work spans generative models, representation learning, vision, and video understanding. Before Google, he completed a PhD at ETH Zurich on efficient data selection and clustering; by 2019, he worked at Google Research in Zurich. He coauthored a large-scale GAN study, a 2019 ICML Best Paper on unsupervised disentangled representations, MLP-Mixer, and PaLI-X. In May 2025, he was a Research Scientist and Gemini video-understanding lead; as of October 2026, he is a Research Director at Google DeepMind leading research teams across video understanding and agentic vision.
- Now at
- Google DeepMind
Timeline
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By 2019
PhD at ETH Zurich
He completes a PhD at ETH Zurich on efficient data selection and clustering before joining Google. By 2019, he works as a researcher at Google Research in Zurich.
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2018–2019
Testing GANs at scale
In 2018, he coauthors A Large-Scale Study on Regularization and Normalization in GANs. The study examines training pitfalls and reproducibility issues, and its revised version is accepted to ICML 2019.
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2019
An ICML Best Paper
In 2019, he coauthors Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations, which wins ICML's Best Paper Award. The study argues that unsupervised learning of disentangled representations is fundamentally impossible without inductive biases on the models and data.
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2021
MLP-Mixer for vision
In 2021, he coauthors MLP-Mixer, a vision architecture built exclusively from multi-layer perceptrons. Its design applies MLPs independently to image patches and across patches, and NeurIPS presents the paper as a poster.
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2024
PaLI-X at CVPR
In 2024, he coauthors PaLI-X, a multilingual vision-and-language model evaluated on image captioning, question answering, document understanding, object detection, and video tasks. The paper reports results across more than 20 vision-and-language benchmarks.
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May 2025
Gemini 2.5 video work
In May 2025, he serves as a Research Scientist and video-understanding lead for Gemini 2.5. Gemini 2.5 combines audio-visual information with code to support video applications.
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As of October 2026
Research Director at Google DeepMind
As of October 2026, he is a Research Director at Google DeepMind, leading research teams across video understanding, agentic vision, and compact encoders for Gemini. In September 2026, he coauthors Google's launch of agentic video understanding, which searches video frames, audio, and transcripts.
Career
- Since 2025Google DeepMindResearch Scientist and video-understanding lead
- From 2019Google ResearchResearcher
Education
- ETH ZurichPhD
Sources and credits
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- Mario Lučić | Research & Gemini Video Demos
- ICML Best Paper Award for Francesco Locatello
- A Large-Scale Study on Regularization and Normalization in GANs
- Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
- MLP-Mixer: An All-MLP Architecture for Vision
- PaLI-X: On Scaling up a Multilingual Vision and Language Model
- Advancing the frontier of video understanding with Gemini 2.5
- Introducing agentic video understanding with Gemini


