深圳又一個數學大獎來了！全球唯一：港中大（深圳）Yurii Nesterov教授榮獲2026年高斯獎

美國東部時間7月23日，有“數學界的奧運會”之稱的2026年國際數學家大會（ICM 2026）正式公布了各類獎項獲獎名單。香港中文大學（深圳）數據科學學院教授、深圳河套學院人工智能理論及系統中心教授Yurii Nesterov榮獲本屆高斯獎，成為自獎項設立以來的全球第六位獲獎者。Yurii Nesterov教授是世界頂尖的優化理論學者，其提出的加速梯度方法等研究成果成為現代機器學習與優化算法的重要基礎，深刻影響了現代數學、計算機科學及人工智能的發展。

Yurii Nesterov教授在大會頒獎現場

高斯獎（Carl Friedrich Gauss Prize）是全球應用數學領域的最高榮譽，與菲爾茲獎、陳省身獎等同為國際數學界的頂級學術獎項。該獎項由國際數學聯盟（IMU）與德國數學學會（DMV）聯合創設，作為國際數學家大會（ICM）重磅核心獎項，代表著全球應用數學領域的最高學術權威與行業認可。

國際數學家大會授予Yurii Nesterov教授的頒獎詞

高斯獎于2006年在國際數學家大會上首次頒發。區別于聚焦純理論研究的數學獎項，高斯獎側重表彰數學成果的落地應用與社會實效，致敬那些依托前沿數學理論，在前沿技術研發、產業商業創新、民生生活改善等領域作出突破性、開創性貢獻的科研工作者。歷屆獲獎者均是引領應用數學學科發展、賦能全社會科技創新的杰出學者。

值得一提的是，因其在凸優化理論方面的奠基性貢獻及其對現代機器學習的深遠影響，Yurii Nesterov教授在今年年初榮獲了美國國家人工智能科學院（National Academy of Artificial Intelligence，NAAI）2026年度 NAAI Academy Award（NAAI學院獎）。該獎項是美國國家人工智能科學院設立的最高榮譽獎項，旨在表彰對人工智能理論體系與核心科學問題作出歷史性貢獻的杰出科學家。

NESTEROV, Yurii

教授

• 香港中文大學（深圳）數據科學學院教授

• 深圳河套學院人工智能理論及系統中心教授
  

• 美國國家科學院外籍院士

• 比利時法語魯汶大學運籌學與計量經濟學中心榮休教授

研究領域：

非線性優化理論與方法、運籌學模型、優化在機器學習與人工智能中的應用

個人簡介：

Yurii Nesterov教授是美國國家科學院外籍院士、歐洲科學院院士、黑山科學院外籍院士。他于1977年至1992年間在莫斯科中央經濟與數學研究所擁有研究職位，并于1993年到2023年期間在比利時法語魯汶大學運籌學與計量經濟學中心擔任教授。

他的研究興趣涉及復雜性問題和解決各種優化問題的有效方法，主要成果分布在凸優化的不同領域：平滑問題的優化方法、多項式時間內點方法、結構優化的平滑技術、二階方法的復雜性理論、大規模問題的優化方法、可實現張量方法。

Nesterov加速方法徹底改變了優化理論，它證明了僅利用梯度信息的一階算法，也能夠比經典梯度下降法實現顯著更快的收斂速度。他提出的算法首次達到了光滑凸優化問題的一階方法所能實現的理論最優收斂速度，成為優化理論發展史上的一個里程碑。這一思想奠定了眾多現代優化算法的基礎，廣泛應用于機器學習、信號處理以及大規模數據分析等領域。如今，Nesterov加速已被TensorFlow和PyTorch等主流深度學習框架廣泛采用，用于訓練大規模神經網絡，并已成為世界各地優化課程的核心教學內容。自問世四十余年來，它始終被公認為數學優化領域最具影響力和最具代表性的重大突破之一。

國際數學家大會(ICM)

國際數學家大會（International Congress of Mathematicians，ICM），是由國際數學聯盟（IMU）主辦的國際數學界規模最大也是最重要的會議，每四年舉行一次。會議是數學家們為了數學交流，展示、研討數學發展的國際性會議，是國際數學界的盛會。大會每四年舉行一次，首屆大會1897年在瑞士蘇黎世舉行，至今已有百余年的歷史，被譽為數學界的奧林匹克盛會。2026年國際數學家大會于7月23日至30日在美國費城舉行。

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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.

（內容來源：香港中文大學（深圳）數據科學學院、深圳河套學院聯合出品）

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