香港中文大学（深圳）Yurii Nesterov教授荣获2026年高斯奖

美国东部时间7月23日，有“数学界的奥运会”之称的2026年国际数学家大会（ICM 2026）正式公布了各类奖项获奖名单。香港中文大学（深圳）数据科学学院教授、深圳河套学院人工智能理论及系统中心教授Yurii Nesterov荣获本届高斯奖，成为自奖项设立以来的全球第六位获奖者。Yurii Nesterov教授是世界顶尖的优化理论学者，其提出的加速梯度方法等研究成果成为现代机器学习与优化算法的重要基础，深刻影响了现代数学、计算机科学及人工智能的发展。

Yurii Nesterov教授在大会颁奖现场

高斯奖（Carl Friedrich Gauss Prize）是全球应用数学领域的最高荣誉，与菲尔兹奖、陈省身奖等同为国际数学界的顶级学术奖项。该奖项由国际数学联盟（IMU）与德国数学学会（DMV）联合创设，作为国际数学家大会（ICM）重磅核心奖项，代表着全球应用数学领域的最高学术权威与行业认可。

国际数学家大会授予Yurii Nesterov教授的颁奖词

高斯奖于2006年在国际数学家大会上首次颁发。区别于聚焦纯理论研究的数学奖项，高斯奖侧重表彰数学成果的落地应用与社会实效，致敬那些依托前沿数学理论，在前沿技术研发、产业商业创新、民生生活改善等领域作出突破性、开创性贡献的科研工作者。历届获奖者均是引领应用数学学科发展、赋能全社会科技创新的杰出学者。

值得一提的是，因其在凸优化理论方面的奠基性贡献及其对现代机器学习的深远影响，Yurii Nesterov教授在今年年初荣获了美国国家人工智能科学院（National Academy of Artificial Intelligence，NAAI）2026年度 NAAI Academy Award（NAAI学院奖）。该奖项是美国国家人工智能科学院设立的最高荣誉奖项，旨在表彰对人工智能理论体系与核心科学问题作出历史性贡献的杰出科学家。

NESTEROV, Yurii

教授

• 香港中文大学（深圳）数据科学学院教授
• 深圳河套学院人工智能理论及系统中心教授
• 美国国家科学院外籍院士
• 比利时法语鲁汶大学运筹学与计量经济学中心荣休教授

研究领域：

非线性优化理论与方法、运筹学模型、优化在机器学习与人工智能中的应用

个人简介：

Yurii Nesterov教授是美国国家科学院外籍院士、欧洲科学院院士、黑山科学院外籍院士。他于1977年至1992年间在莫斯科中央经济与数学研究所拥有研究职位，并于1993年到2023年期间在比利时法语鲁汶大学运筹学与计量经济学中心担任教授。

他的研究兴趣涉及复杂性问题和解决各种优化问题的有效方法，主要成果分布在凸优化的不同领域：平滑问题的优化方法、多项式时间内点方法、结构优化的平滑技术、二阶方法的复杂性理论、大规模问题的优化方法、可实现张量方法。

Nesterov加速方法彻底改变了优化理论，它证明了仅利用梯度信息的一阶算法，也能够比经典梯度下降法实现显著更快的收敛速度。他提出的算法首次达到了光滑凸优化问题的一阶方法所能实现的理论最优收敛速度，成为优化理论发展史上的一个里程碑。这一思想奠定了众多现代优化算法的基础，广泛应用于机器学习、信号处理以及大规模数据分析等领域。如今，Nesterov加速已被TensorFlow和PyTorch等主流深度学习框架广泛采用，用于训练大规模神经网络，并已成为世界各地优化课程的核心教学内容。自问世四十余年来，它始终被公认为数学优化领域最具影响力和最具代表性的重大突破之一。

国际数学家大会(ICM)

国际数学家大会（International Congress of Mathematicians，ICM），是由国际数学联盟（IMU）主办的国际数学界规模最大也是最重要的会议，每四年举行一次。会议是数学家们为了数学交流，展示、研讨数学发展的国际性会议，是国际数学界的盛会。大会每四年举行一次，首届大会1897年在瑞士苏黎世举行，至今已有百余年的历史，被誉为数学界的奥林匹克盛会。2026年国际数学家大会于7月23日至30日在美国费城举行。

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Professor Yurii Nesterov of CUHK-Shenzhen Receives 2026 Gauss Prize

On July 23 (Eastern Time), the 2026 International Congress of Mathematicians (ICM 2026), often described as the "Olympics of Mathematics," officially announced the complete list of prize recipients in Philadelphia. Professor Yurii Nesterov, Professor at the School of Data Science at The Chinese University of Hong Kong, Shenzhen and the Center for AI Theory and Systems of Shenzhen Loop Area Institute, was awarded the Gauss Prize becoming the sixth recipient since the prize‘s establishment. Professor Yurii Nesterov is a world-leading expert in optimization theory. His pioneering research, most notably the accelerated gradient method, underpins modern machine learning and optimization algorithms, and has profoundly shaped the advancement of modern mathematics, computer science, and artificial intelligence.

Professor Yurii Nesterov at the Award Ceremony

The Carl Friedrich Gauss Prize stands asthe highest honor in the field of applied mathematics. Ranking alongside the Fields Medal and the Chern Medal, it is recognized as one of the most prestigious academic awards in the global mathematics community. Jointly established by the International Mathematical Union (IMU) and the German Mathematical Society (DMV), this flagship award is presented at the International Congress of Mathematicians (ICM), representing the pinnacle of academic authority and professional recognition in worldwide applied mathematics research.

Award Citation for Professor Yurii Nesterov at the ICM

The prize was first conferred at the 2006 International Congress of Mathematicians. Unlike other mathematics awards that focus primarily on pure theoretical research, the Gauss Prize specifically honors outstanding scholars for the practical implementation and societal impact of their mathematical achievements. It recognizes researchers who leverage cutting-edge mathematical theories to deliver groundbreaking and transformative contributions to advanced technological development, industrial and commercial innovation, and improvements in public well-being. All past laureates are distinguished academics who lead the advancement of applied mathematics and drive scientific and technological innovation across society.

Notably, earlier this year, Professor Yurii Nesterov was awarded the 2026 NAAI Academy Award by the National Academy of Artificial Intelligence (NAAI) in recognition of his foundational contributions to convex optimization theory and its profound impact on modern machine learning. The NAAI Academy Award represents the highest honor of the National Academy of Artificial Intelligence. It recognizes scientists whose work has reshaped the intellectual foundations of artificial intelligence.

NESTEROV, Yurii

Professor

• Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen
• Professor of Center for AI Theoretical Foundation and Systems，Shenzhen Loop Area Institute
• International Member of the National Academy of Sciences
• Emeritus Professor, Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCLouvain), Belgium

Research Areas:

Theory and Methods of Nonlinear Optimization, Models of Operations Research, Applications of Optimization in Machine Learning and Artificial Intelligence

Biography:

Prof. Yurii Nesterov is an International Member of the National Academy of Sciences (NAS), a Member of Academiae Europaeae, and a Foreign Member of the Montenegrin Academy of Science. He held a research position at the Central Economic and Mathematical Institute in Moscow from 1977 to 1992, and served as a professor at the Center for Operations Research and Econometrics (CORE) at the Catholic University of Louvain (UCL), Belgium, from 1993 to 2023.

His research interests are related to complexity issues and efficient methods for solving various optimization problems. The main results are obtained in different areas of Convex Optimization: optimal methods for smooth problems, polynomial-time interior-point methods, smoothing technique for structural optimization, complexity theory for second-order methods, optimization methods for huge-scale problems, implementable tensor methods.

Nesterov's acceleration transformed optimization by showing that a simple first-order method could converge dramatically faster than classical gradient descent while using only gradient information. His algorithm achieved the theoretically optimal convergence rate for smooth convex optimization, a milestone that fundamentally reshaped the field. The ideas behind it have become the foundation of many modern optimization algorithms used in machine learning, signal processing, and large-scale data analysis. Today, Nesterov acceleration is implemented in major deep learning frameworks such as TensorFlow and PyTorch, is widely used to train large-scale neural networks, and is taught in virtually every graduate course on optimization. More than four decades after its introduction, it remains one ofthe most influential and celebrated breakthroughs in mathematical optimization.

The International Congress of Mathematicians

Hosted by the International Mathematical Union (IMU), the International Congress of Mathematicians (ICM) ranks asthe largest and most vital global gathering for mathematics professionals. Held once every four years, this premier global congress enables mathematicians across the globe to exchange insights, showcase cutting-edge research and discuss disciplinary progress, earning its reputation as the "Olympics of Mathematics". The inaugural congress convened in Zurich, Switzerland, back in 1897, marking a century-long legacy of international mathematical exchange. The ICM 2026 will run from July 23 to 30 in Philadelphia, the United States.

香港中文大学（深圳）数据科学学院、深圳河套学院联合出品