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Honors and Awards

Jorge Nocedal Selected for Lagrange Prize

Honor awarded every three years for an outstanding contribution in continuous optimization

Northwestern Engineering’s Jorge Nocedal has been selected for the Lagrange Prize in Continuous Optimization by the Mathematical Optimization Society (MOS) and the Society for Industrial and Applied Mathematics (SIAM). 

Nocedal, Walter P. Murphy Professor of Industrial Engineering and Management Sciences and (by courtesy) engineering sciences and applied mathematics and also the director of the Center for Optimization and Statistical Learning, along with two collaborators, was recognized for the 2018 paper “Optimization Methods for Large-Scale Machine Learning.” The work provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning applications. It has been cited more than 1,500 times. 

Jorge Nocedal

Co-authors are Leon Bottou, a Facebook artificial intelligence researcher, and Frank E. Curtis, an associate engineering professor at Lehigh University.

The Lagrange Prize in Continuous Optimization is awarded every three years for an outstanding contribution in the area of continuous optimization published in the six calendar years prior to the award year. 

The honor is the latest for Nocedal, who was elected to the National Academy of Engineering (NAE) in 2020. Nocedal also received the John von Neumann Theory Prize from the Institute for Operations Research and Management Sciences in 2017.

Nocedal’s research interests include optimization, machine learning, optimal control, software, and scientific computing.

The prize will be awarded at the 2021 SIAM Annual Meeting, scheduled to be held virtually from July 19-23. 

MOS is an international organization dedicated to the promotion and the maintenance of high professional standards in the subject of mathematical optimization. SIAM fosters the development of applied mathematical and computational methodologies needed in various application areas.