Speakers

The 2nd International Conference on AI Scientists (ICAIS 2026)

October 17–19, 2026 | Zhongguancun Academy, Beijing, China

Keynote Speakers

Omar M. Yaghi

Prof. Omar M. Yaghi

2025 Nobel Laureate in Chemistry

Tsinghua University

Jack J. Dongarra

Prof. Jack J. Dongarra

2021 ACM A.M. Turing Award Laureate

University of Tennessee

Michael Levitt

Prof. Michael Levitt

2013 Nobel Laureate in Chemistry

Stanford University

Miguel Nicolelis

Prof. Miguel Nicolelis

Pioneer of Brain-Machine Interfaces

French Academy of Sciences & Brazilian Academy of Sciences

Chris Sander

Prof. Chris Sander

Pioneer of Computational Biology and Bioinformatics

Harvard Medical School

Invited Talk Speakers

Xiao Ma

Xiao Ma

From Microscopic Particles to the Macroscopic World: Revisiting Hilbert's Sixth Problem

Assistant Professor at the University of Michigan. A core collaborator of 2026 Fields Medalist Yu Deng, Ma co-authored the rigorous derivation of the Boltzmann equation from hard-sphere particle systems with Yu Deng and Zaher Hani, overcoming a century-old challenge related to Hilbert's Sixth Problem.

Jian Tang

Jian Tang

Partnering with a Turing Award Laureate: Reimagining Drug Discovery with Generative AI

Tenured Associate Professor at Mila and CIFAR AI Chair Professor in Canada; founder of BioGeometry. His work focuses on geometric deep learning and generative AI for protein design and antibody drug discovery.

Jiancheng Yang

Jiancheng Yang

From Europe's Leading AI Network: Exploring Spatial Intelligence and Life Sciences

Independent PI at the ELLIS Institute Finland and Tenure-Track Assistant Professor of Intelligent Systems at Aalto University. His research focuses on generative AI, agents, multimodal learning and world models for healthcare AI.

Lingfei Wu

Lingfei Wu

Decoding How Innovation Works: The Science Behind Breakthroughs

Associate Professor of Information Science at the University of Pittsburgh, Lingfei Wu studies the mechanisms underlying scientific innovation through the integration of big data, complexity science, and artificial intelligence. His research has helped uncover how breakthrough ideas emerge and evolve, including the co-development of the Disruption Index, the first validated metric for identifying breakthrough ideas.

His work has been published in leading journals including Nature, Science, and PNAS, and has been featured in The New York Times, The Atlantic, and Harvard Business Review. He is a recipient of the NSF CAREER Award and an NIH R01 grant.