2026.04.14 Colloquia Seminars
| Speaker |
Prof. Christoph Ortner, University of British Columbia |
| Title |
Mathematics and Physics Foundations of Machine Learning Atomistic Models |
| Time |
2026.04.23 15:30-16:30 |
| Venue |
N219 |
| Abstract |
The integration of machine learning into the traditional modelling workflows is replacing decades-old ad hoc approximations (e.g., in constitutive laws) leading to new models that far outstrip their predecessors in accuracy and transferability. "Pure" ML approaches are rarely successful but remarkable results can be achieved when integrated with domain knowledge. My talk will focus on the atomistic scale where the development of reduced-order interaction laws, in particular interatomic potentials, has made immense progress. My aim in this talk is to show how electronic structure modelling, analysis and numerical analysis ideas contribute to both the construction and understanding of new machine learning surrogate models, in particular when complex multi-physics such as charge equilibration or magnetism come into the picture. I will also discuss how this field is changing the focus of electronic structure calculations. |
| Biography |
Christoph Ortner，加拿大不列颠哥伦比亚大学（UBC）数学系教授、副系主任（科研），长期从事应用数学、数值分析与科学计算研究，主要聚焦原子尺度建模、多尺度方法及机器学习在电子结构与分子模拟中的应用。曾获欧洲研究委员会（ERC）2013年Starting Grant 和2019 年 Consolidator Grant，曾获得 Whitehead Prize（2015年）与 Oberwolfach John Todd Award（2017年），并入选加拿大皇家学会新锐学者学院。现任 SIAM Multiscale Modeling & Simulation、European Journal of Applied Mathematics、Journal of Computational Mathematics、Acta Applicandae Mathematicae等杂志的编委。 | |
