What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Artificial intelligence
- Mechanical engineering
Efstratios N. Pistikopoulos spends much of his time researching Mathematical optimization, Optimization problem, Process, Stochastic programming and Optimal design.
His biological study spans a wide range of topics, including Algorithm, Parametric programming and Integer.
His research investigates the connection between Optimization problem and topics such as Controllability that intersect with problems in Process design and Process control.
His Process research incorporates themes from Fractionating column, Minification, Control engineering, Environmental impact assessment and Process engineering.
Efstratios N. Pistikopoulos interconnects Scheduling and Model predictive control in the investigation of issues within Control engineering.
His study in Optimal design is interdisciplinary in nature, drawing from both Batch processing and Optimal control.
His most cited work include:
- The explicit linear quadratic regulator for constrained systems (2502 citations)
- Environmentally conscious long-range planning and design of supply chain networks (348 citations)
- Optimal design of dynamic systems under uncertainty (215 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Mathematical optimization, Control theory, Model predictive control, Control engineering and Optimization problem.
His Mathematical optimization study combines topics in areas such as Parametric programming and Nonlinear programming.
Control theory is frequently linked to Process in his study.
His Model predictive control study frequently links to other fields, such as Nonlinear system.
While the research belongs to areas of Control engineering, Efstratios N. Pistikopoulos spends his time largely on the problem of Process control, intersecting his research to questions surrounding Process design.
His studies in Optimization problem integrate themes in fields like Global optimization and Integer.
He most often published in these fields:
- Mathematical optimization (33.76%)
- Control theory (16.96%)
- Model predictive control (16.80%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (33.76%)
- Model predictive control (16.80%)
- Process (11.89%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Model predictive control, Process, Optimization problem and Process engineering.
His work focuses on many connections between Mathematical optimization and other disciplines, such as Deep learning, that overlap with his field of interest in Artificial neural network.
His Model predictive control research includes elements of Set and Control theory, Nonlinear system.
His work deals with themes such as Energy consumption, Reliability engineering, Operability, Systems engineering and Risk analysis, which intersect with Process.
His Optimization problem study also includes
- Quadratic programming which intersects with area such as Quadratic equation,
- Linear programming which intersects with area such as Integer.
His work is dedicated to discovering how Process engineering, Renewable energy are connected with Wind power, Energy storage and Scheduling and other disciplines.
Between 2015 and 2021, his most popular works were:
- An overview of process systems engineering approaches for process intensification: State of the art (90 citations)
- Towards the integration of process design, control and scheduling: Are we getting closer? (64 citations)
- POP – Parametric Optimization Toolbox (50 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Artificial intelligence
- Electrical engineering
Mathematical optimization, Process, Optimization problem, Model predictive control and Nexus are his primary areas of study.
His studies deal with areas such as Job shop scheduling and Integer as well as Mathematical optimization.
His Process research incorporates themes from Energy consumption, Reliability engineering, Operability and Risk analysis.
His Optimization problem research is multidisciplinary, relying on both Linear programming, Multi-objective optimization, Stochastic programming and Bounded function.
Efstratios N. Pistikopoulos combines subjects such as Continuous stirred-tank reactor, Control theory, Electric power system, Control engineering and Process design with his study of Model predictive control.
His work on Second-order cone programming as part of general Convex optimization research is frequently linked to Quadratically constrained quadratic program, Active set method and Nonlinear programming, bridging the gap between disciplines.
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