Daniel Bienstock

He is studying problems related to analysis and operations of power transmission networks, including analysis of the vulnerabilities of electrical power grids, a topic of increasing relevance to society and also one of fascinating mathematical complexity which he explores in a book recently published by SIAM.

The mathematics of power grids is nonlinear and nonconvex, as well as stochastic. A second recent thrust focuses on mixed-integer nonlinear programming problems and more generally polynomial optimization problems.

The physics of power networks is nonlinear and subject to noise due to ambient conditions, ill-defined control actions (including human actions), and imprecise device operation. This subjects mathematical algorithms to complex forms of data uncertainty. Yet engineering practice demands precise answers and actions. An interesting topic is the verification of near-feasibility or infeasibility of candidate solutions to algebraic systems.

Bienstock received a BA in mathematics from Brandeis University in 1982 and a PhD in operations research from Massachusetts Institute of Technology in 1982. He received the Khachiyan Prize in Optimization in 2022. He is a fellow of INFORMS and was a plenary speaker at the 2005 SIAM Optimization Conference and a semi-plenary speaker at ISMP 2006. He has received a Presidential Young Investigator Award and an IBM Faculty Partnership Award. He joined the faculty of Columbia Engineering in 1989 after working in combinatorics and optimization research at Bellcore.

Research Areas

• Power Systems
• Smart Electric Energy (Smart Grids)
• Quantum Computing
• Renewable Energy
• Optimization
• Risk Management
• Energy & Power
• Large-scale Optimization
• Urban Logistics