What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Operating system
Pascal Van Hentenryck mainly focuses on Mathematical optimization, Constraint programming, Constraint logic programming, Constraint satisfaction and Theoretical computer science.
Pascal Van Hentenryck interconnects Quadratic equation, AC power, Nonlinear programming and Vehicle routing problem in the investigation of issues within Mathematical optimization.
His biological study spans a wide range of topics, including Lattice, Algebra, Code and Large neighborhood search.
His research integrates issues of Set, Logic programming and Constraint satisfaction problem in his study of Constraint logic programming.
His Constraint satisfaction study incorporates themes from Fifth-generation programming language, Discrete mathematics and Inductive programming, Functional logic programming.
His Theoretical computer science research incorporates themes from Combinatorial search, Combinatorial optimization, Heuristics and Search algorithm.
His most cited work include:
- Constraint satisfaction in logic programming (1130 citations)
- The Constraint Logic Programming Language CHIP. (508 citations)
- Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (495 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Constraint programming, Theoretical computer science, Constraint satisfaction and Constraint logic programming.
The concepts of his Mathematical optimization study are interwoven with issues in Algorithm, Scheduling, Electric power system and Vehicle routing problem.
His Constraint programming research is multidisciplinary, incorporating perspectives in Programming language, Local search, Inductive programming, Fifth-generation programming language and Combinatorial optimization.
His study in Logic programming, Prolog and Nondeterministic algorithm falls within the category of Theoretical computer science.
His study in Constraint satisfaction concentrates on Concurrent constraint logic programming and Constraint graph.
His research integrates issues of Constraint satisfaction problem and Local consistency in his study of Constraint logic programming.
He most often published in these fields:
- Mathematical optimization (36.66%)
- Constraint programming (23.03%)
- Theoretical computer science (14.40%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (36.66%)
- Differential privacy (3.45%)
- Optimization problem (8.83%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Differential privacy, Optimization problem, Artificial intelligence and Operations research.
He works in the field of Mathematical optimization, focusing on Bilevel optimization in particular.
His study on Differential privacy also encompasses disciplines like
- Information sensitivity and related Data mining,
- Inference, Computation and Flow most often made with reference to Distributed algorithm.
His Optimization problem study combines topics in areas such as Context and Electricity market.
The Artificial intelligence study which covers Machine learning that intersects with Travel behavior.
In his research on the topic of Operations research, Consistency is strongly related with Transit.
Between 2018 and 2021, his most popular works were:
- Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods. (25 citations)
- Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (24 citations)
- Dynamic Compressor Optimization in Natural Gas Pipeline Systems (19 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Operating system
Pascal Van Hentenryck focuses on Mathematical optimization, Differential privacy, Artificial intelligence, Optimization problem and Electric power system.
The study incorporates disciplines such as Constraint programming, Convergence, Discretization, Scheduling and Flooding in addition to Mathematical optimization.
His Differential privacy research also works with subjects such as
- Obfuscation that intertwine with fields like Data processing, Power grid, Electric power transmission, Load management and Information privacy,
- Information sensitivity that connect with fields like Data mining, Aggregate, Consistency, Key and Obfuscation,
- Distributed algorithm that connect with fields like Flow,
- Power flow, which have a strong connection to Inference, Computation and Bilevel optimization.
His work in the fields of Deep learning overlaps with other areas such as Mixed logit.
His studies deal with areas such as Stackelberg competition and Electricity market as well as Optimization problem.
His Electric power system research focuses on Renewable energy and how it connects with Generator, Block, Nonlinear control and Gas compressor.
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