What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Computer network
- Algorithm
The scientist’s investigation covers issues in Mathematical optimization, Integer programming, Combinatorics, Graph and Power grid.
Mathematical optimization and Network control are commonly linked in his work.
His research in Integer programming intersects with topics in Multi-commodity flow problem, Flow network, Computation, Scale and Upper and lower bounds.
His work in Computation tackles topics such as Network planning and design which are related to areas like Telecommunications network.
His Upper and lower bounds research includes themes of Branch and cut, Quadratic programming, Criss-cross algorithm and Knapsack problem.
He has researched Graph in several fields, including Characterization, Minor, Isomorphism and Treewidth.
His most cited work include:
- Computational study of a family of mixed-integer quadratic programming problems (322 citations)
- Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (296 citations)
- Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty ∗ (289 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Combinatorics, Discrete mathematics, Integer programming and Optimization problem.
In his works, Daniel Bienstock undertakes multidisciplinary study on Mathematical optimization and Stochastic process.
His Combinatorics study combines topics from a wide range of disciplines, such as Bounded function and Knapsack problem.
His work in the fields of Knapsack problem, such as Continuous knapsack problem, overlaps with other areas such as Covering problems.
His Discrete mathematics research includes elements of Polynomial optimization and Relaxation.
Daniel Bienstock works in the field of Integer programming, focusing on Branch and cut in particular.
He most often published in these fields:
- Mathematical optimization (42.75%)
- Combinatorics (28.99%)
- Discrete mathematics (23.91%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (42.75%)
- Discrete mathematics (23.91%)
- Linear programming (7.25%)
In recent papers he was focusing on the following fields of study:
His main research concerns Mathematical optimization, Discrete mathematics, Linear programming, Polynomial optimization and Stochastic process.
Mathematical optimization is closely attributed to Theory of computation in his study.
Daniel Bienstock interconnects Graph and Linear programming relaxation in the investigation of issues within Discrete mathematics.
The concepts of his Linear programming study are interwoven with issues in Complex number, Flow and Nonlinear system.
His Polynomial optimization research is multidisciplinary, incorporating elements of Treewidth, Polynomial inequalities and Dimension.
His Computation study incorporates themes from Control system and Robustness.
Between 2017 and 2021, his most popular works were:
- Strong NP-hardness of AC power flows feasibility (20 citations)
- Chance-Constrained Unit Commitment With N-1 Security and Wind Uncertainty (11 citations)
- LP Formulations for Polynomial Optimization Problems (11 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Computer network
- Algebra
Daniel Bienstock mainly investigates Mathematical optimization, Stochastic process, Discrete mathematics, Linear programming and Topology.
His study on Mathematical optimization is mostly dedicated to connecting different topics, such as Control.
Variance, Work, Control system and Computation are fields of study that intersect with his Stochastic process study.
His work in the fields of Treewidth overlaps with other areas such as Class.
He has included themes like Time complexity, Deep learning, Artificial intelligence, Exponential function and Polynomial in his Linear programming study.
Topology is intertwined with AC power, Flow system and Materials science in his study.
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