Workshop on Cognitive Reasoning

Scope and Aims

The Workshop on Cognitive Reasoning brings together researchers in psychology, neuroscience, and artificial intelligence to explore how humans and machines learn, represent the world, and reason about physical events and other minds. The series connects experimental evidence with computational models to address these questions in both biological and artificial systems.

Launched in 2024, the workshop creates a setting for research talks, discussion, and exchange across disciplines. Past programs have spanned attention, causal inference, social intelligence, brain simulation, world models, neural decoding, intuitive physics, and the human context of AI. Together, they reflect a common ambition: to understand the principles of intelligence and bring that understanding into the design of artificial systems.

Learning, Representations, and Reasoning

A central focus is how intelligent systems acquire knowledge and use it to understand their surroundings. This includes the representations that organize perception and experience, the processes that support inference, and the ways these processes guide action. Behavioral studies describe what people perceive, learn, and infer; neuroscience examines the biological processes that support those abilities; and computational models make assumptions about learning and reasoning explicit.

Brains and Machines

The series brings biological and artificial intelligence into the same discussion. Cognitive and neural findings can suggest useful questions for AI research, while artificial systems can help formulate and examine hypotheses about the mind and brain. Comparing their capabilities and limitations offers a way to ask which principles are shared and which depend on the system being studied. The 2025 theme, Cognitive Scaling: Bridging Brains and Machines, developed this dialogue through talks on structured world models, biological learning, neural accounts of reasoning, and human-centered AI.

Interdisciplinary Discussion

Researchers working on related problems often use different concepts, measurements, and standards of evidence. The workshop offers an opportunity to explain those choices, compare approaches, and identify questions that benefit from collaboration across fields. Its scope also includes how AI systems interact with people and how human-centered perspectives shape their development and evaluation. Research talks, discussion sessions, and informal exchange make room for these connections to develop.

Chairs Across the Series

Conference and program chairs are listed below, with the editions they served shown beneath each name.

Conference Chairs

Song-Chun Zhu Song-Chun Zhu

Peking University

2024 · 2025 · 2026

Yizhou Wang Yizhou Wang

Peking University

2024 · 2025 · 2026

Yanchao Bi

2026

Program Chairs

Yixin Zhu Yixin Zhu

Peking University

2024 · 2025 · 2026

Jiayu Zhan Jiayu Zhan

Peking University

2025

Qian Wang Qian Wang

Peking University

2025

Huihui Zhang

2026

Yujia Peng Yujia Peng

2026

Speakers Across the Series

Featured speakers from the 2024 and 2025 editions are listed alphabetically by surname, then given name. Each year links to that speaker’s contribution in the corresponding program; affiliations are those listed for the archived editions. The full programs and speaker lists are available in the annual archives.

Kai Du Kai Du

Peking University

2024

Zaifeng Gao Zaifeng Gao

Zhejiang University

2025

Mohsen Jamali Mohsen Jamali

Harvard Medical School

2025

Yuanning Li Yuanning Li

ShanghaiTech University

2025

Huan Luo Huan Luo

Peking University

2025

Mark Nitzberg Mark Nitzberg

University of California, Berkeley

2024 · 2025

Yujia Peng Yujia Peng

Peking University

2024

Federico Rossano Federico Rossano

University of California, San Diego

2025

Mowei Shen Mowei Shen

Zhejiang University

2024

Xinwei Sun Xinwei Sun

Fudan University

2024

Kexin Yuan Kexin Yuan

Tsinghua University

2024

Jiayu Zhan Jiayu Zhan

Peking University

2024

Chi Zhang Chi Zhang

Beijing Institute for General Artificial Intelligence

2024

Ruyuan Zhang Ruyuan Zhang

Shanghai Jiao Tong University

2025

Fangwei Zhong Fangwei Zhong

Beijing Normal University

2024

Chen Zhou Chen Zhou

University of Glasgow

2025

Xiaolin Zhou Xiaolin Zhou

East China Normal University

2024

Lusha Zhu Lusha Zhu

Peking University

2024

Past Workshops

The annual archive preserves each edition’s program and materials so that the conversations remain accessible beyond the workshop itself.