直播时间：2025年5月20日（周二）20:00-21:30

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北京时间5月20日晚八点，iCANX Youth Talks第98期邀请到了清华大学化学工程系长聘副教授王笑楠、北京鑫研微末生物科技有限公司联合创始人兼CSO张家燕、深势科技创始人兼首席科学家张林峰担任主讲，晶泰科技联合创始人赖力鹏担任研讨嘉宾，北京大学教授张海霞担任主持人，期待你一起加入这场知识盛宴。

【嘉宾介绍】

王笑楠

清华大学

AI赋能能源化工新材料发现与过程设计

【Abstract】

Chemical engineering plays a crucial role in the global economy and requires continuous innovation to address evolving environmental and societal challenges. While traditional experimental approaches have driven significant advancements in chemical materials and process design over the past century, their reliance on trial-and-error experimentation remains time-consuming and resource-intensive. Artificial intelligence (AI) has become pivotal in chemical materials innovation and development, promising to catalyze breakthroughs by integrating with traditional process technologies. This talk focuses on AI-driven design of chemical materials and processes, bridging fundamental principles of chemical process systems engineering with cutting-edge AI and machine learning (ML) methodologies. Key innovative include: (1) Developing a data-driven and knowledge-fused active learning method for chemical materials to address complex, non-parameterizable systems; (2) Establishing a precision intelligent synthesis and characterization platform to enhance research efficiency and accuracy; and (3) Creating a multi-scale digital twin and low-carbon intelligent system to integrate complex data and knowledge across scales, delivering industrial and societal impact. In summary, this talk highlights how AI-powered methodologies can accelerate discovery and optimization in chemical engineering, paving the way for sustainable and intelligent innovations.

发展新质生产力，推动经济社会高质量发展，需打破原有产业界限，向智能化、绿色化、融合化方向不断演进。而化工、能源、环境等领域面临着一个共同挑战：如何将微观尺度物质特性与宏观尺度工程应用有效关联，实现高效精准的预测、优化和控制。对此， AI 驱动的能源化工新材料与低碳过程设计可以结合大数据挖掘、深度主动学习、基础模型优化、数据增强等智能方法，有效指导新材料、新工艺、新系统的开发，探索高效的碳捕集、利用和催化转化体系。通过融合高通量计算和高通量实验等关键技术，结合机械自动化平台，高效开发关键材料和催化剂。本报告将探讨如何：1）构建数据驱动融合知识的新分子新材料建模与优化方法；2）发展关键新材料与器件的精准智能合成及表征策略；3）建立多尺度数字孪生与低碳智联系统，实现智能材料研制平台的转化应用。未来展望将从跨尺度、多模态、可通用、可解释 AI 的角度深入研究智能科学，建立大规模模块化领域人工智能基础模型，以数据为桥梁，实现理、实、算、数一体化闭环发展，迈向面向低碳绿色发展的通用智能。

【BIOGRAPHY】

Dr. Xiaonan Wang is currently an associate professor in the Department of Chemical Engineering at Tsinghua University and an adjunct associate professor at the National University of Singapore (NUS). She received her BEng from Tsinghua University in 2011 and PhD from University of California, Davis in 2015. After working as a postdoctoral research associate at Imperial College London, she joined NUS as an assistant professor since 2017 and became an associate professor at Tsinghua and NUS since 2021. Her research focuses on the development of intelligent computational methods including multi-scale modelling, optimization, data analytics and machine learning for applications in advanced materials, energy, environmental and manufacturing systems to support smart and sustainable development. She is leading a Smart Systems Engineering research group at NUS and Tsinghua and also the director of the Intelligent Chemical Engineering Research Centre. She has published more than 170 peer-reviewed papers, with more than 11,000 citations and H index 62. She is an editorial board member of 10 SCI journals e.g., Applied Energy, Advanced Intelligent Systems. She was recognized as a Clarivate Highly Cited Researcher, World’s Top 2% Scientists, Cell Press Women Scientist Award, Young Beijing Scholar, AIChE-SLS Outstanding Young Principal Investigator, IChemE Global Awards Young Researcher finalist and selected for Royal Society International Exchanges Award, as well several best paper awards. 

王笑楠，清华大学化学工程系长聘副教授、博导，智能化工研究中心主任。新加坡国立大学荣誉副教授、博导，带领团队长期从事AI+能源化工新材料的研究和应用。在Nat. Mach. Intell.、Nat. Synth.、JACS等期刊发表论文170余篇，被引11000余次，H-index 62。主持 “新一代人工智能”国家科技重大专项“化学材料AI大模型赋能碳中和”（任首席科学家，项目负责人），入选科睿唯安2024年度“全球高被引科学家”、全球学者终身学术影响力榜、连续四年被Elsevier评为全球前2% 顶尖科学家。担任Applied Energy等十本国际期刊副主编和编委，获美国化学会可持续化学与工程讲席奖、Cell Press年度中国女科学家、青年北京学者、中国化工学会侯德榜化工科学技术奖“青年奖”等荣誉。

张家燕

北京鑫研微末生物科技有限公司

冷冻电镜+AI：引领结构生物学的未来范式

【ABSTRACT】

Cryo-electron microscopy (cryo-EM) is a transformative technology for structural analysis in biomedicine. However, its high cost, technical complexity, and limited throughput have restricted widespread adoption. In this talk, I will introduce our work at Nanomega CryoAI Corp, a company I co-founded with UCLA’s Prof. Jeff Miller (National Academy of Sciences) and Prof. Hong Zhou (a world leader in cryo-EM). Our team has developed cutting-edge algorithms such as IsoNet and TomoNet, along with high-throughput CryoET in situ imaging platforms and AI-powered fully automated structural workflows. These innovations are accelerating drug discovery and validating AI4Science designs. Our clients include top pharmaceutical companies, AI4S enterprises, and leading global universities. With structure as the foundation and AI as the engine, we aim to drive structural biology toward a future that is visualizable, intelligent, and scalable.

冷冻电镜是生物医药结构解析的重要突破手段，但因设备昂贵、技术门槛高、效率低下，限制了其广泛应用。本次分享将介绍与UCLA院士Jeff Miller及冷冻电镜领军人物Hong Zhou教授共同创立的Nanomega CryoAI Corp在“冷冻电镜+人工智能”融合领域的研究与技术转化。我们开发了如IsoNet、TomoNet等算法，构建了高通量CryoET原位成像平台，和AI赋能的全流程自动化结构解析工作流，助力药物研发和AI4Science结构验证。已成功服务于创新药企、AI4Science企业与全球多所高校。我们希望以结构为基、AI为翼，引领结构生物学向“可视化+智能化+规模化”迈进。

【BIOGRAPHY】

Dr. Jiayan Zhang holds a Ph.D. in Molecular Biology from UCLA and is the Co-founder and CSO of Beijing Xinyan Weimo Biotechnology Co., Ltd. and Nanomega CryoAI Corp. She was named a Hurun U30 Entrepreneurship Leader. Mentored by Nobel-associated scholars Prof. Jeff Miller and cryo-EM pioneer Prof. Hong Zhou, Dr. Zhang specialized in viral and in situ structural analysis. She has published over 10 peer-reviewed papers in Nature Communications, eLife, Cell Discovery, and others, and has served as a peer reviewer for multiple journals. She received numerous honors including the UCLA Dissertation Year Fellowship and Whitcome Fellowship. Dr. Zhang brings strong entrepreneurial and strategic acumen, having worked as a Senior Life Sciences Specialist at L.E.K. Consulting and served as CEO of a strategy consulting firm, where she advised dozens of IPO-stage companies on global expansion. Her venture has established partnerships with several world-leading tech corporations. Dr. Zhang is now focused on scaling the industrial application of CryoEM + AI, building intelligent scientific infrastructure for the future of life sciences. 

张家燕博士，UCLA分子生物学博士，北京鑫研微末生物科技有限公司联合创始人兼CSO，胡润U30创业领袖。师从诺奖门下UCLA Jeff Miller院士和冷冻电镜权威Hong Zhou教授。曾在UCLA深耕病毒和原位结构解析，在Nature Communications、eLife、Cell Discovery等期刊上发表10余篇科研论文，参与多篇期刊的审稿工作，并荣获UCLA博士论文奖学金、Whitcome Fellowship等多项荣誉。她具有丰富的创业与商业咨询经验，曾任L.E.K.管理咨询生命科学高级专家，为全球领先药企和PE基金提供战略支持；曾担任战略咨询公司CEO，服务数十家IPO企业的出海战略。所创与多家全球顶尖科技公司建立合作。现致力于推动“冷冻电镜+AI”技术产业化，加速科学智能基础设施的全球布局。

张林峰

深势科技创始人兼首席科学家

AI for Science未来的一年、三年、五年

【ABSTRACT】

General intelligence, embodied intelligence, and scientific intelligence are undergoing deep integration this year. In this sharing, I will introduce how AI deeply integrates with the three most fundamental tasks in scientific research - "reading", "calculating", and "doing" - by combining specific practices at DP Technology and AI for Science Institute, Beijing. This will demonstrate how such integration accelerates scientific discovery and drives the development of future industries. For students aspiring to engage in scientific research or entrepreneurship in this wave, I will also share the opportunities and challenges I foresee based on my personal experience.

通用智能、具身智能、科学智能三者正在今年深度融合。在这个分享中，我将结合在深势科技和科学智能研究院的具体实践，介绍AI如何与科学研究中最基本的“读”“算”“做”三大任务深度结合，进而推动科学发现的加速和未来产业的发展。对于有志于在这波浪潮中深入科研或创业的同学，我也将结合个人经历分享我所看到的接下来的机遇和挑战。

【BIOGRAPHY】

Linfeng Zhang is the founder and Chief Scientist of DP Technology, as well as the Director of the AI for Science Institute, Beijing. He holds a Bachelor of Science degree from Peking University and a Ph.D. in Applied Mathematics from Princeton University. Linfeng has long been dedicated to interdisciplinary research in AI for Science, achieving significant results in machine learning, computational physical chemistry, materials, and drug design. He has been consistently listed in Stanford University's "World's Top 2% Scientists" ranking for multiple years. As a core developer, Linfeng has led the creation of a series of micro-scale simulation algorithms and corresponding open-source software. In 2020, DeePMD won the ACM Gordon Bell Prize, the highest honor in high-performance computing, and was also selected as one of China's Top 10 Scientific Breakthroughs of 2020 by academicians of the Chinese Academy of Sciences and Engineering. In early 2025, Linfeng and his team released Uni-3DAR, the world's first cross-scale 3D large model, unifying microscopic and macroscopic 3D worlds through autoregressive modeling. 

张林峰，深势科技创始人兼首席科学家，北京科学智能研究院（AI for Science Institute, Beijing）院长。张林峰先后获得北京大学理学学士及普林斯顿大学应用数学博士学位。林峰长期致力于 AI for Science 跨学科领域的问题研究，在机器学习、计算物理化学、材料与药物设计等领域成果丰富，并连续多年登上斯坦福大学发布的“全球前2%顶级科学家名录 ”。林峰还作为核心开发者，领导开发了一系列微尺度仿真算法及相应开源软件。2020年，DeePMD 获得高性能计算领域最高奖 ACM 戈登贝尔奖 ，该成果也入选了由两院院士评选的2020年度中国十大科技进展 。2025年初，林峰带领团队，发布国际首个跨尺度3D大模型Uni-3DAR，用自回归统一微观与宏观的3D世界。

【主持人】

赖力鹏

晶泰科技联合创始人

【研讨嘉宾】

张海霞

北京大学