What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Computer network
- Control theory
Na Li spends much of his time researching Mathematical optimization, Demand response, Smart grid, Nash equilibrium and Control theory.
His work deals with themes such as Convex relaxation and Microgrid, which intersect with Mathematical optimization.
His Nash equilibrium study combines topics in areas such as Bidding and Supply.
He interconnects Economic dispatch, Control, Control area and Power control in the investigation of issues within Control theory.
As a part of the same scientific family, he mostly works in the field of Demand curve, focusing on Price elasticity of demand and, on occasion, Distributed algorithm.
In his work, Optimization problem, Rate of convergence, Gradient descent and Convex function is strongly intertwined with Smoothness, which is a subfield of Distributed algorithm.
His most cited work include:
- Optimal demand response based on utility maximization in power networks (797 citations)
- Design and Stability of Load-Side Primary Frequency Control in Power Systems (348 citations)
- Exact Convex Relaxation of Optimal Power Flow in Radial Networks (275 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Mathematical optimization, Control theory, Optimization problem, Rate of convergence and Distributed algorithm.
The Relaxation research Na Li does as part of his general Mathematical optimization study is frequently linked to other disciplines of science, such as Demand response, therefore creating a link between diverse domains of science.
His Control theory research is multidisciplinary, relying on both Control and AC power.
His Optimization problem study combines topics from a wide range of disciplines, such as Passivity, Dynamical systems theory, Dynamical system, Convergence and Convex function.
His Convex function research includes elements of Exponential stability and Applied mathematics.
His study explores the link between Distributed algorithm and topics such as Function that cross with problems in Smoothness.
He most often published in these fields:
- Mathematical optimization (38.89%)
- Control theory (21.11%)
- Optimization problem (18.33%)
What were the highlights of his more recent work (between 2019-2021)?
- Mathematical optimization (38.89%)
- Optimization problem (18.33%)
- Control theory (21.11%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Optimization problem, Control theory, Control and Rate of convergence.
His Mathematical optimization research includes themes of Distributed generation and Multi-agent system.
His research in Optimization problem intersects with topics in Control engineering, Dynamical systems theory and Cyber-physical system.
His studies deal with areas such as Convergence and AC power as well as Control theory.
His study focuses on the intersection of Convergence and fields such as Convex function with connections in the field of Applied mathematics and Convex optimization.
His Rate of convergence research integrates issues from Gradient descent, Graph, Theoretical computer science and Communications protocol.
Between 2019 and 2021, his most popular works were:
- Accelerated Distributed Nesterov Gradient Descent (61 citations)
- Optimal Distributed Feedback Voltage Control Under Limited Reactive Power (21 citations)
- On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication (15 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Computer network
- Control theory
Na Li focuses on Applied mathematics, Convex function, Convergence, Exponential stability and Control theory.
His study in Applied mathematics is interdisciplinary in nature, drawing from both Equivalence, Linear system and Convex optimization.
The Convex function study combines topics in areas such as Linear programming, Linear map and Gradient descent.
His research in Convergence intersects with topics in Dynamical systems theory, Acceleration, Hybrid system, Discretization and Optimization problem.
His studies in Exponential stability integrate themes in fields like LTI system theory and Linear dynamical system.
His research investigates the connection with Control theory and areas like AC power which intersect with concerns in Voltage control, Robustness and Power flow.
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