报告人：张林峰 教授 (深势科技)

时 间：2023年9月21日(周四)下午14：00-16：00

地 点：良乡校区，理学楼B203会议室

摘要：

Rapid advancements in artificial intelligence (AI) and machine learning (ML) have led to significant transformations in the field of materials modeling and simulation. In this talk, we will delve into the latest breakthroughs and advancements in AI-assisted materials modeling, placing emphasis on the transition from multi-scale methods to pre-trained models. The potential of AI-driven approaches to address the inherent complexity and multi-scale nature of molecular systems will be discussed, alongside case studies that demonstrate how these methods are enabling more accurate and efficient simulations. The transition to and application of pre-trained models will then be scrutinized through various examples. Finally, we will contemplate the future of materials modeling and the role of AI and cloud computing in shaping this field.

简历：

Linfeng Zhang, a researcher at the AI for Science Institute in Beijing and founder of DP Technology, holds a background in applied mathematics from Princeton University and physics from Peking University. His work concentrates on the interdisciplinary field of AI for Science, contributing to machine learning, computational physics and chemistry, and materials and drug design. Linfeng is the major developer of DeePMD-kit, an open-source software for molecular simulation, and has been promoting the DeepModeling community for AI for Science enthusiasts. His efforts have led to several significant projects and recognition, including the ACM Gordon Bell Prize in 2020, and a feature on the cover of Forbes Asia's 30 Under 30 list for 2022.

联系方式：weiguo7@bit.edu.cn

邀 请 人：郭伟

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