Frontiers in AI for Science
Graduate / advanced undergrad
Graduate / advanced undergrad
Course Introduction
Established by Peking University’s School of Materials Science and Engineering, this forum is offered as an Engineering Innovation Education course. It aims to broaden students’ perspectives on the frontiers of interdisciplinary artificial intelligence and cultivate innovative talent in materials science and related fields. Responding to national strategic priorities and the University’s development of New Engineering disciplines, the course focuses on global advances in AI for Science and invites leading international scholars in artificial intelligence, materials science, and related fields to present their work. Through sustained exposure to scientific and industrial frontiers, students develop an international perspective, a deeper understanding of AI4S, and the ability to lead technological innovation in materials-related fields.
Course Features
- Interdisciplinary perspective—connecting shared questions across mathematics, molecules, materials, proteins, and scientific experiments.
- Lectures by active experts—featuring researchers and industry leaders working at the forefront of the field.
- Open to all disciplines—designed for graduate students and advanced undergraduates regardless of major.
- Continuously updated—offered every semester, with topics evolving alongside the field.
Upcoming Lectures
The following lectures are planned; topics and dates will be updated as the course progresses:
| Lecture | Speaker | Topic | Affiliation | Date |
|---|---|---|---|---|
| 27 | 赵怡程 | High-Throughput Experiment and Pre-Trained Model for Accelerating the Development of Photovoltaic Materials | School of Integrated Circuits Science and Technology, University of Electronic Science and Technology of China; Professor | 2026-11-27 |
| 28 | TBD | TBD | TBD | 2026-12-11 |
| 29 | 袁粒 | Multimodal Generation and Its Applications in AI for Science | School of AI for Science, Peking University Shenzhen Graduate School; Researcher | 2026-12-25 |
Previous Lectures
The series has hosted 26 lectures covering AI foundations, molecular and materials discovery, protein design, physics-based drug discovery, molecular simulation, scientific knowledge discovery, generative models, microscopy, embodied intelligence for experiments, physical agents, mathematics, photography, spatiotemporal AI, and automated reaction discovery.
| Lecture | Speaker | Topic | Affiliation | Date |
|---|---|---|---|---|
| 1 | 张林峰 | AI for Science: From Innovation to Deployment | DP Technology; Beijing Academy of Artificial Intelligence for Science | 2025-02-27 |
| 2 | 周嘉欢 | Introduction to Artificial Intelligence | Wangxuan Institute of Computer Technology, Peking University | 2025-03-13 |
| 3 | 朱丹青 | Machine Learning in Drug Discovery and Protein Design | Hong Kong University of Science and Technology | 2025-03-27 |
| 4 | 杨 仝 | Large-Model Distillation and Cross-Domain Applications | School of Computer Science, Peking University | 2025-04-10 |
| 5 | 罗三中 | AI Molecular Catalysis | Department of Chemistry, Tsinghua University | 2025-04-24 |
| 6 | 陈云天 | Automated Discovery of Scientific Knowledge with AI | Eastern Institute of Technology, Ningbo | 2025-05-08 |
| 7 | 季 威 | An Introduction to AI for Materials Science | School of Physics, Renmin University of China | 2025-05-22 |
| 8 | 储卫民 | Applications and Impact of AI in Photography | Professional landscape photographer | 2025-06-05 |
| 9 | 张 锦 | AI-Driven Transformation of Materials Science Research | Peking University | 2025-09-19 |
| 10 | 张文彬 | AI-Enabled Protein Topology Engineering | College of Chemistry and Molecular Engineering, Peking University | 2025-10-17 |
| 11 | 高 鑫 | AI for Complex Materials Systems | School of Materials Science and Engineering, Peking University | 2025-10-31 |
| 12 | 胡丕丕 | From Diffusion to Flow: Generative Models and Scientific Discovery | Beijing Institute of Mathematical Sciences and Applications | 2025-11-14 |
| 13 | 朱 戎 | AI-Accelerated Discovery of Functional Molecules and Reactions | College of Chemistry, Peking University | 2025-11-28 |
| 14 | 周伯文 | General AI for Scientific Research: Trends and Opportunities | Department of Electronic Engineering, Tsinghua University | 2025-12-12 |
| 15 | 王珊珊 | Machine Learning for Atomic-Scale Microscopy of Materials | National University of Defense Technology | 2025-12-26 |
| 16 | 罗 毅 | Scalable AI Robotic Chemist Systems | University of Science and Technology of China | 2026-03-13 |
| 17 | 崔颖璐 | Computational Protein Design and Enzyme Catalysis | Institute of Microbiology, Chinese Academy of Sciences | 2026-03-27 |
| 18 | 田永鸿 | Embodied Intelligence for Scientific Experiments | Peking University Shenzhen Graduate School | 2026-04-10 |
| 19 | 赵晓续 | AI-Driven Electron Microscopy | School of Materials Science and Engineering, Peking University | 2026-04-24 |
| 20 | 董 彬 | Perspectives on Artificial Intelligence and Mathematics | Beijing International Center for Mathematical Research, Peking University | 2026-05-08 |
| 21 | 王笑楠 | Toward Autonomous Scientific Discovery with Foundation Models and AI Agents | Department of Chemical Engineering, Tsinghua University | 2026-05-22 |
| 22 | 郑 宇 | Spatiotemporal AI: Bringing Artificial Intelligence into the Physical World | JD.com | 2026-06-05 |
| 23 | 来鲁华 | Drug Discovery Based on Physics-Based Models and Artificial Intelligence | College of Chemistry and Molecular Engineering, Peking University; Professor | 2026-09-18 |
| 24 | 王 涵 | Artificial Intelligence for Molecular Simulation | Institute of Applied Physics and Computational Mathematics; Researcher | 2026-10-16 |
| 25 | 廖矿标 | Making Chemical Reaction Space Searchable: From Automated Experiments to AI-Driven Reaction Discovery | Guangzhou National Laboratory; Researcher | 2026-10-30 |
| 26 | 周大权 | Exploring General-Purpose Physical Agents in the Wild | School of AI for Science, Peking University Shenzhen Graduate School; Researcher | 2026-11-13 |
Previous lecture information is compiled from the course record. Future sessions will be added as the course develops.
Want to Know More?
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