Beijing Institute of Mathematical Sciences and Applications

Jie Du

Tieyan Liu

Thursday, October 27, 2022 3:00 PM - 4:00 PM

JCY-3

Tencent 807 850 470 ()

In the past decades, AI has achieved notable success in computer vision, speech recognition, and natural language understanding. However, mimicking human’s vision, speech, and language capabilities is just a shallow aspect of AI. It neglects the fact that we, as human beings, are unique because of our courage and ability to discover and change the world. AI-for-Science aims at building powerful tools to help natural scientists to better discover and change the world. Specifically, AI-for-Science assumes that the physical world can be theoretically characterized by fundamental scientific equations, usually at very large scale. It also acknowledges that there is always a gap between theory and reality, and the evidence of the gap can be found in experimental data. No one has the capability to efficiently solve all those complex scientific equations, analyze those massive experimental data, or create a closed loop between them. This is exactly where AI could play a disruptive role. As a showcase of such disruptions, I will introduce several research projects at MSR AI4Science, including Graphormer, an AI model for molecular dynamics simulation, DeepVortexNet, a neural PDE solver for fluid dynamics, SciGPT, an AI language model to automatically extract knowledge from scientific literature, and LorentzNet, and equivariant AI model to detect new particles from large-scale jet data. After introducing these works, I will also discuss some future trends of AI-for-Science research.

刘铁岩博士，微软杰出首席科学家、微软亚洲研究院副院长、微软研究院科学智能中心亚洲区负责人。他是国际电气电子工程师学会（IEEE）会士、 国际计算机学会（ACM）会士、亚太人工智能学会（AAIA）会士。他被聘为清华大学、香港科技大学、中国科技大学、华中科技大学兼职教授、诺丁汉大学荣誉教授。 刘博士的先锋性研究促进了机器学习与信息检索之间的融合，被公认为“排序学习”领域的代表人物。近年来他在深度学习、强化学习、工业智能、科学智能等方面颇有建树，在顶级国际会议和期刊上发表论文数百篇，被引用数万次。他的研究工作多次获得最佳论文奖、最高引用论文奖、研究突破奖，并被广泛应用在微软的产品和在线服务中，如必应（Bing）搜索、微软广告、Windows、Xbox、Azure等。 刘博士曾担任WWW/WebConf、SIGIR、NeurIPS、ICLR、ICML、IJCAI、AAAI、KDD、ACL等十余个国际顶级学术会议的大会主席、程序委员会主席或（资深）领域主席；ACM TOIS、ACM TWEB、IEEE TPAMI等国际期刊副主编。 他的团队于2017年开源了LightGBM，目前已成为Kaggle比赛、KDD Cup和产业决策过程中最受欢迎的机器学习工具之一；于2018年在中英新闻翻译任务上达到了人类专家水平，并于次年获得WMT机器翻译比赛8项冠军；于2019年研发了麻将AI Suphx，在国际知名麻将平台“天凤”上荣升十段，稳定段位显著超越人类顶级选手；2021年发布了用于分子模拟的Graphormer模型，并在KDD Cup分子建模比赛和催化剂设计开放挑战赛中力拔头筹。 刘铁岩博士毕业于清华大学，先后获得电子工程系学士、硕士及博士学位。