中国科学院院士 · 中国 AI for Science 奠基者Academician CAS · Father of AI for Science in China
deep-learningsystems
北京大学与普林斯顿数学家,中科院院士。他把机器学习确立为求解高维偏微分方程与多体物理的工具,共同创立 Deep Potential 方法与 Deep Ritz/深度 BSDE 求解器,并培养了如今把该领域产业化的一代人(深势科技张林峰等)。2021 年的文章为「AI for Science」在中国定名。
Mathematician at Peking University and Princeton, member of the Chinese Academy of Sciences. A founding figure of AI for Science: he framed machine learning as a tool for solving high-dimensional PDEs and many-body physics, co-created the Deep Potential method and Deep Ritz/BSDE solvers, and mentored the generation now commercialising the field (Zhang Linfeng at DP Technology, Tang Linpeng at Moqi). His 2021 essay on \"AI for Science\" gave the movement its name in China.