主讲人简介：
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9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190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等多个国家重点和重大基金。荣获加拿大应用与工业数学会科研突破奖（CAIMS-SCMAI Research Prize），阿尔伯塔大学杰出导师奖，约瑟夫·米歇尔指导奖，美国数学生物科学研究所杰出青年学者奖，以及加拿大国家基金科研加速资助奖等。
内容摘要：
Stoichiometric principles provide a rigorous, law-based backbone for building mechanistic models that are robust and empirically testable through conservation and physiological constraints. In this talk, I will introduce stoichiometric models that resolve key biological paradoxes by explicitly tracking elemental and quota-driven limitations, then demonstrate how data-driven components can (i) learn missing processes, (ii) improve short-term forecasting, and (iii) enable real-time monitoring. Methane biogenesis in oil sands tailings serves as a central application: we couple stoichiometric biodegradation dynamics with ML-enabled monitoring to better predict emissions trajectories. This research contributes to the broader goal of carbon neutrality.
