4 sources
One of the clearest DeepMind names for understanding planning-heavy reinforcement learning, from AlphaZero and MuZero to newer reasoning and tool-use work around Gemini.
Researcher Profile
Editor reviewedIoannis Antonoglou
Gemini (multimodal foundation models)
Co-lead for reinforcement learning techniques on Gemini
A high-signal reinforcement-learning researcher whose work sits on the path from AlphaGo-era planning systems to Gemini-era reasoning and post-training techniques.
Organizations
Google DeepMind
About This Page
This profile is meant to help you get oriented quickly: why this researcher matters, what to read first, and where to explore next.
Known For
The ideas, systems, and research directions that make this person worth knowing.
01
AlphaGo and AlphaZero-style planning systems
02
Model-based reinforcement learning
03
Reinforcement-learning techniques in Gemini
04
Gemini (multimodal foundation models)
05
Gemini: A Family of Highly Capable Multimodal Models
06
Gemini
Start Here
Canonical papers, project pages, or repositories that anchor this profile.
Supporting Sources
Additional links that help verify and flesh out this profile.
Related Researchers
People worth exploring next because they share topics, labs, or source material with this profile.
4 sources
Important for understanding how multilingual NLP, translation, and multimodal reasoning meet inside production-scale frontier systems rather than staying separate research tracks.
Start HereRadu Soricut
4 sources
A good researcher to follow for the infrastructure side of frontier language models, especially mixture-of-experts scaling, instruction tuning, and the data systems that make very large models usable.
4 sources
Important for the branch of DeepMind research that connects control, world models, and modern agent behavior rather than treating them as separate eras.
4 sources
One of the more useful people to study for the Gemini era because his work spans both the text-core of multimodal frontier models and the optimization tricks that make those systems cheaper and more stable to train.
4 sources
A high-signal researcher for understanding the modern scaling playbook, especially around compute-optimal training, retrieval-augmented language models, and the text side of Gemini-era multimodal systems.