What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- The Internet
His scientific interests lie mostly in Mathematical optimization, Distributed computing, Network congestion, Computer network and Distributed algorithm.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Schedule, Smart grid, Convex optimization, Computation and Demand response.
The study incorporates disciplines such as Stability, Throughput, Random access, Telecommunications network and Internet protocol suite in addition to Distributed computing.
His work on TCP tuning as part of general Network congestion research is often related to Utility maximization problem, thus linking different fields of science.
His Distributed algorithm study integrates concerns from other disciplines, such as AC power and Asynchronous communication.
His Queueing theory research includes elements of Active queue management and Random early detection.
His most cited work include:
- Optimization flow control—I: basic algorithm and convergence (1851 citations)
- Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures (1242 citations)
- REM: active queue management (963 citations)
What are the main themes of his work throughout his whole career to date?
Steven H. Low mostly deals with Mathematical optimization, Control theory, Computer network, Distributed computing and Electric power system.
His biological study spans a wide range of topics, including Convex optimization, Distributed algorithm and Power flow.
His Distributed algorithm research integrates issues from Demand response and Random access.
His studies deal with areas such as Network congestion, Resource allocation, Telecommunications network, The Internet and Scheduling as well as Distributed computing.
In general Network congestion study, his work on TCP tuning often relates to the realm of Utility maximization problem, thereby connecting several areas of interest.
His Electric power system study combines topics in areas such as Distributed generation and AC power.
He most often published in these fields:
- Mathematical optimization (33.55%)
- Control theory (16.45%)
- Computer network (16.02%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (33.55%)
- Electric power system (15.37%)
- Electric vehicle (6.28%)
In recent papers he was focusing on the following fields of study:
Steven H. Low mainly investigates Mathematical optimization, Electric power system, Electric vehicle, Control theory and Power flow.
Steven H. Low works in the field of Mathematical optimization, namely Optimization problem.
His Electric power system research incorporates themes from Tree structure, Transmission and Automatic frequency control.
His Electric vehicle study also includes fields such as
- Simulation which is related to area like Open source and Data-driven,
- Model predictive control which intersects with area such as Scheduling, Energy, Robust control, Control system and Parameterized complexity,
- Battery which is related to area like Real-time computing.
His Control theory study incorporates themes from Node and Power control.
His Power flow research is multidisciplinary, relying on both Mathematical analysis, Shunt, Network topology, Constraint and Relaxation.
Between 2018 and 2021, his most popular works were:
- System level synthesis (52 citations)
- Distributed Frequency Control With Operational Constraints, Part I: Per-Node Power Balance (36 citations)
- On Identification of Distribution Grids (31 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Operating system
- The Internet
His primary areas of study are Electric power system, Mathematical optimization, Control theory, Control theory and Key.
His research in Electric power system intersects with topics in Optimization problem, AC power, Differential privacy and Transmission.
Steven H. Low undertakes interdisciplinary study in the fields of Mathematical optimization and Expression through his works.
His studies in Control theory integrate themes in fields like Tree structure, Cascading failure, Power control and Automatic Generation Control.
His work is dedicated to discovering how Control theory, Optimal control are connected with Equilibrium point and other disciplines.
His work investigates the relationship between Key and topics such as Scalability that intersect with problems in Industrial engineering, Reinforcement learning, Control, Telecommunications network and Energy management.
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