2026 NAAI Artificial Intelligence Exploration Award

The NAAI Artificial Intelligence Exploration Award, presented by the National Academy of Artificial Intelligence (NAAI), recognizes scholars whose research has opened new directions in the scientific foundations and exploratory frontiers of artificial intelligence.

The award honors pioneering contributions across theoretical and interdisciplinary domains of AI, including machine learning theory, causal inference, reinforcement learning, intelligent systems, swarm intelligence, and uncertainty-aware decision frameworks. By recognizing original and forward-looking research, the award highlights work that expands the conceptual boundaries of artificial intelligence and shapes its future development.

The 2026 Global Final Awardees represent leading researchers from major universities and research institutions across Asia, Europe, North America, and Australia. Their work has significantly advanced the theoretical understanding and technological foundations of intelligent systems.

2026 Global Final Awardees

1. Yongduan Song

Chongqing University — China

For pioneering contributions to intelligent control and AI-integrated dynamic systems.

2. Zhi-Hua Zhou

Nanjing University — China

For foundational work in machine learning theory and ensemble learning paradigms.

3. Balaraman Ravindran

Indian Institute of Technology Madras — India

For theoretical advances in reinforcement learning and sequential decision-making.

4. Pushpak Bhattacharyya

Indian Institute of Technology Bombay — India

For pioneering research in language intelligence and semantic representation.

5. Chua Tat-Seng

National University of Singapore — Singapore

For foundational contributions to knowledge-driven artificial intelligence.

6. Toby Walsh

UNSW Sydney — Australia

For theoretical work on rational agents and multi-agent intelligence.

7. Anton van den Hengel

University of Adelaide — Australia

For advancing perceptual intelligence and representation learning.

8. Judea Pearl

University of California, Los Angeles — United States

For establishing the foundations of causal artificial intelligence.

9. Leslie Valiant

Harvard University — United States

For defining the theoretical boundaries of computational learnability.

10. Zoubin Ghahramani

University of Cambridge — United Kingdom

For foundational work in Bayesian learning and uncertainty-aware AI.

11. Karl Friston

University College London — United Kingdom

For proposing a unified theoretical framework for intelligent systems.

12. Marco Dorigo

Université libre de Bruxelles — Belgium

For pioneering swarm intelligence and collective artificial systems.

13. Thomas Dietterich

Oregon State University — United States

For contributions to reliable and system-level artificial intelligence.

14. Doina Precup

McGill University / Mila — Canada

For theoretical advances in hierarchical reinforcement learning.

15. Roger Grosse

University of Toronto — Canada

For foundational research in probabilistic representation learning.

16. Bernard De Baets

Ghent University — Belgium

For foundational contributions to fuzzy preference modeling, ordinal data analysis, and uncertainty-aware intelligent decision systems.