2025 Winner(s)
- Renato D.C. Monteiro, Georgia Institute of Technology
A leading figure in continuous optimization for decades, Monteiro has combined deep and far-reaching theory and complexity analysis with practical algorithm design.
An early breakthrough was Monteiro’s polynomial-time analysis of higher-order interior-point methods for linear programming. His short-step primal-dual algorithms quickly became fundamental for large-scale convex optimization, while in parallel, his notion of optimal partitions illuminated solution structure and algorithmic behavior: These elegant ideas continue to shape the field today. Monteiro went on to introduce the Monteiro-Zhang search direction family, a foundational polynomial-time interior-point framework for semidefinite programming that unified and generalized earlier methods and resolved long-standing theoretical questions about the Alizadeh-Haeberly-Overton direction in particular, which continues to influence contemporary algorithm design broadly.
A subsequent breakthrough, the Burer-Monteiro low-rank method opened the door to solving massive semidefinite programs through nonlinear optimization. Previously intractable problems in combinatorial optimization, machine learning, control systems, and statistical modeling, became solvable. Monteiro’s associated open-source solver remains a standard tool in disciplines spanning chemical and electrical engineering, computer vision, and statistical learning. His widespread influence grew further with works such as a pioneering complexity bound for the popular ADMM method, and his ideas continue to drive advances in large-scale and distributed optimization. Along the way, he has made crucial contributions concerning linear complementarity, central path curvature, and statistical dimension reduction.
Throughout his career, along with field-shaping intellectual contributions, Monteiro has also helped guide the theoretical optimization community through professional service, editorial leadership, and student mentorship. He is a singular force in continuous optimization.
Purpose of the Award
Committee Chair
Adrian Lewis
Cornell University
Have questions? Please email: [email protected]
The John von Neumann Theory Prize is awarded annually to a scholar (or scholars in the case of joint work) who has made fundamental, sustained contributions to theory in operations research and the management sciences. The award is given each year at the INFORMS Annual Meeting if there is a suitable recipient. Although the Prize is normally given to a single individual, in the case of accumulated joint work, the recipients can be multiple individuals.
The Prize is awarded for a body of work, typically published over a period of several years. Although recent work should not be excluded, the Prize typically reflects contributions that have stood the test of time. The criteria for the Prize are broad, and include significance, innovation, depth, and scientific excellence.
The award is $5,000, a medallion and a citation.
2026 Submission Deadline: June 1, 2026
The Prize Committee is currently seeking nominations, which should be in the form of a letter (preferably email) addressed to the prize committee chair (below), highlighting the nominee's accomplishments. Although the letter need not contain a detailed account of the nominee's research, it should document the overall nature of his or her contributions and their impact on the profession, with particular emphasis on the prize's criteria. The nominee's curriculum vitae, while not mandatory, would be helpful.
About the Award/Namesake
John von Neumann was a brilliant mathematician, synthesizer, and promoter of the stored program concept, whose logical design of the IAS became the prototype of most of its successors - the von Neumann Architecture. von Neumann was invited to visit Princeton University in 1930, and when the Institute for Advanced Studies was founded there in 1933, he was appointed to be one of the original six Professors of Mathematics, a position which he retained for the remainder of his life. Postwar von Neumann concentrated on the development of the Institute for Advanced Studies (IAS) computer and its copies around the world. His work with the Los Alamos group continued and he continued to develop the synergism between computers capabilities and the needs for computational solutions to nuclear problems related to the hydrogen bomb.