Shabbir Ahmed Awarded 2018 Farkas Prize by INFORMS Optimization Society

Primary tabs

The 2018 Farkas Prize of the INFORMS Optimization Society has been awarded to Shabbir Ahmed, the Anderson-Interface Chair and professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE). The society cited Ahmed’s “fundamental contributions to the theory and practice of stochastic discrete optimization.”

“Congratulations to Shabbir on this major recognition of his work,” said ISyE School Chair Edwin Romeijn. “This prestigious award is presented annually to a mid-career researcher for outstanding contributions to the field of optimization over the course of their career. Shabbir’s research in developing methods for large-scale optimization problems, and their applications in energy and other networked systems, has made a significant impact in his field. This honor is very well deserved.”

“I am deeply honored and humbled to be selected for the 2018 Farkas Prize,” said Ahmed. “Sincere thanks to the esteemed prize committee for choosing me. Throughout my research career, I have been very fortunate to work with many excellent collaborators and Ph.D. students, and this award is a great recognition of our joint research accomplishments.”

Ahmed’s theoretical contributions to stochastic programming have been broad and deep. These have improved the understanding of multistage stochastic programming and consistent formulations of risk preferences, and provided bounds on sample average approximation solutions to non-convex chance-constrained optimization problems. His contributions to mathematical programming computation address some of the most difficult but important topics in the field with wide applicability in production systems, energy systems, health care, transportation, security, and more. His ability to exploit integer-programming structures that arise in stochastic programming is a recurring theme in his research.

Of particular importance is: (i) Ahmed’s work that allows combining of single-scenario mixed-integer programming inequalities in a multi-stage stochastic program; (ii) his research on using integer programming, with knapsack inequalities, to solve a class of probabilistically constrained linear programs; and, (iii) his recent work on extending decomposition algorithms for solving large-scale multi-stage stochastic integer programs.

About Anderson-Interface Chair and Professor Shabbir Ahmed

Ahmed received his Ph.D. from the University of Illinois in 2000, and his dissertation on stochastic integer programming won the Dantzig Prize from INFORMS. Since then, he has become a recognized worldwide leader in the integration of two challenging methodologies – stochastic programming and integer programming – essential for solving important optimization problems in energy, supply chain, transportation, and finance.

Ahmed’s research has been supported by federal agencies such as the Advanced Research Program Agency - Energy (ARPA-E), the Air Force Office of Scientific Research, the National Science Foundation, and the Office of Naval Research; as well as by industrial organizations such as ExxonMobil, IBM, and Samsung.

He has served as the chair of the Stochastic Programming Society (2007-10), and as a vice-chair (Stochastic Programming) of the INFORMS Optimization Society (2006-08). His honors include the INFORMS Computing Society Prize, the National Science Foundation CAREER award, two IBM Faculty Awards, and the Coca-Cola Early Career Professorship from ISyE. Ahmed is an associate editor for Mathematical Programming A, Mathematical Programming C, Operations Research, and Operations Research Letters. He is a senior member of IEEE and a Fellow of INFORMS.


  • Workflow Status:Published
  • Created By:Shelley Wunder-Smith
  • Created:10/18/2018
  • Modified By:Andy Haleblian
  • Modified:10/19/2018


  • No categories were selected.