Dear colleagues,

The INFORMS Computing Society is pleased to announce the recipients of the 2025 ICS Prize, awarded for outstanding contributions at the interface of computing and operations research. Due to the exceptional submissions received this year, the committee recommended the recognition of two submissions as co-winners of the ICS Prize, as well as one submission as recipient of Honorable Mention.

Co-Winner

Alper Atamtürk, Andrés Gómez, and Shaoning Han

• Citation: Professors Alper Atamtürk, Andrés Gómez, and Shaoning Han are recognized with the 2025 INFORMS Computing Society Prize for their pioneering contributions to modeling and solving mixed-integer quadratic optimization problems.
• Through a sequence of influential papers, they developed a powerful convexification toolkit, including submodularity-based inequalities, rank-one relaxations, and 2×2 convexifications, that transformed once intractable mixed-integer quadratic models into scalable algorithms. Their methods elegantly combine theory and computation, enabling advances in machine learning, signal processing, computer vision, and finance.

Co-Winner 

Jason Altschuler and Pablo Parrilo

• Citation: Professors Jason Altschuler and Pablo Parrilo are recognized with the 2025 INFORMS Computing Society Prize for their pioneering work on accelerating gradient descent through stepsize hedging.
• Their research introduced the novel concepts of Silver Stepsizes, stepsize hedging, and multi-step descent, demonstrating that acceleration is possible in gradient descent solely through dynamic choice of stepsizes, a breakthrough overturning decades of conventional wisdom. By developing innovative techniques such as recursive gluing, they established improved convergence rates and inspired a new line of research in the design and analysis of optimization algorithms. Their work has already had significant impact across convex optimization and machine learning.

Honorable Mention

Shabbir Ahmed (in memoriam), Yongpei Guan, Ruiwei Jiang, and Weijun Xie

• Citation: Professors Shabbir Ahmed (in memoriam), Yongpei Guan, Ruiwei Jiang, and Weijun Xie are recognized with an Honorable Mention for the 2025 INFORMS Computing Society Prize for their fundamental contributions to the computation of distributionally robust chance-constrained programs (DRCCPs).
• Their research established the computational complexity of DRCCPs, developed exact reformulations under phi-divergence and Wasserstein ambiguity sets, and designed both exact and approximation algorithms with provable guarantees. By introducing novel inequalities and cutting-plane methods, they enabled the solution of large-scale, real-world problems in supply chain management, healthcare, and energy systems. Their work has set the standard and shaped the research direction in this important area of risk-averse optimization.

 

I would like to thank the 2025 INFORMS ICS Prize Committee for their diligent work:

• George Lan (Chair), Georgia Institute of Technology
• Güzin Bayraksan, Ohio State University
• Grani Hanasusanto, University of Illinois Urbana-Champaign
• Andrew Trapp, Worcester Polytechnic Institute

Please join us at the ICS business meeting during the INFORMS 2025 Annual Meeting in Atlanta on Monday, October 27, to recognize the contribution of our colleagues, thank our volunteers for this prize committee, and remember Shabbir once more. 

You can find below the references to the winning materials of each of the three submissions:

Winning materials

Co-winner: Alper Atamtürk, Andrés Gómez, and Shaoning Han

Alper Atamtürk, Andrés Gómez, Strong formulations for quadratic optimization with M-matrices and indicator variables, Mathematical Programing, Ser. B (2018) 170:141–176.

Alper Atamtürk, Andrés Gómez, Submodularity in Conic Quadratic Mixed 0–1 Optimization, Operations Research, Vol. 68, No. 2, March–April 2020, pp. 609–630.

Alper Atamtürk, Andrés Gómez, Safe Screening Rules for l0-Regression from Perspective Relaxations, Proceedings of the 37th International Conference on Machine Learning, PMLR 119, 2020.

Alper Atamtürk, Andrés Gómez, Shaoning Han, Sparse and Smooth Signal Estimation: Convexification of l0-Formulations, Journal of Machine Learning Research 22 (2021) 1-43.

Shaoning Han, Andrés Gómez, Alper Atamtürk, 2 × 2-Convexifications for convex quadratic optimization with indicator variables, Mathematical Programming (2023) 202:95–134.

Alper Atamtürk,  Andrés Gómez, Rank-one Convexification for Sparse Regression, Journal of Machine Learning Research (2025) 1-50.

 

Co-winner: Jason Altschuler and Pablo Parrilo

Jason M. Altschuler and Pablo A. Parrilo. 2025. Acceleration by Stepsize Hedging: Multi-Step Descent and the Silver Stepsize Schedule. J. ACM 72, 2, Article 12 (March 2025), 38 pages. https://doi.org/10.1145/3708502.

Jason M. Altschuler · Pablo A. Parrilo, Acceleration by stepsize hedging: Silver Stepsize Schedule for smooth convex optimization, Mathematical Programming, https://doi.org/10.1007/s10107-024-02164-2, 2024.

 

Honorable Mention: Shabbir Ahmed (in memoriam), Yongpei Guan, Ruiwei Jiang, and Weijun Xie

Ruiwei Jiang, Yongpei Guan, Data-driven chance constrained stochastic program, Math. Program., Ser. A (2016) 158:291–327 DOI 10.1007/s10107-015-0929-7.

Weijun Xie. Shabbir Ahmed, Ruiwei Jiang, Optimized Bonferroni approximations of distributionally robust joint chance constraints, Mathematical Programming (2022) 191:79–112 https://doi.org/10.1007/s10107-019-01442-8.

Weijun Xie, On distributionally robust chance constrained programs with Wasserstein distance, Mathematical Programming (2021) 186:115–155 https://doi.org/10.1007/s10107-019-01445-5.

Weijun Xie, Shabbir Ahmed, Bicriteria Approximation of Chance-Constrained Covering Problems, Operations Research, Vol. 68, No. 2, March–April 2020, pp. 516–533

Sincerely,

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Thiago Serra
Assistant Professor of Business Analytics, University of Iowa
INFORMS Computing Society Chair (2024-2025)
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