Stoichiometric theory includes multiple biological scales from elements to ecosystems, and allows the construction of robust mechanistic, predictive, and empirically testable models via rigorous chemical and physical laws. Experimental and fundamental evidence motivates the application of this microscopic approach to understand macroscopic phenomena. I will introduce a series of stoichiometric models and their novel dynamics that resolve some biological paradoxes and lead to new insights. Selected new mathematical development will be briefly described. “True” model validation will be presented in contrast to conventional methods with many freedoms. I will briefly mention my recent expansion on a new graduate program and research of data science and machine learning.

报告人简介：王皓，加拿大生物数学首席科学家（Tier 1 Canada Research Chair in Mathematical Biosciences），加拿大阿尔伯塔大学终身正教授，阿尔伯塔大学数学生态学和传染病学交叉研究实验室主任。现任七个国际生物数学和动力系统主流杂志的主编或编委，已在高水平SCI期刊发表论文150余篇。在化学计量学，动物认知移动，环境污染毒素，微生物分解，物种入侵，传染病传播机制和预测等都做出了开创性和突破性研究。目前主导加拿大Alliance Missions等多个国家重点基金。荣获美国数学生物科学研究所杰出青年学者奖，阿尔伯塔大学杰出导师奖，约瑟夫·米歇尔指导奖，加拿大国家基金科研加速资助奖。