Ernest S. Kuh

What is he best known for?

The fields of study he is best known for:

• Mathematical analysis
• Algorithm
• Electrical engineering

Ernest S. Kuh mainly focuses on Algorithm, Routing, Mathematical optimization, Topology and Very-large-scale integration. His research integrates issues of Benchmark, Parallel computing and Linear equation in his study of Algorithm. The concepts of his Routing study are interwoven with issues in Chip and Steiner tree problem.

The study incorporates disciplines such as Graph theory and Sequence in addition to Mathematical optimization. His Topology research is multidisciplinary, incorporating perspectives in Circuit diagram, Equivalent circuit and Active networking. His work carried out in the field of Very-large-scale integration brings together such families of science as Network topology and Theoretical computer science.

His most cited work include:

• Basic circuit theory (697 citations)
• Efficient Algorithms for Channel Routing (494 citations)
• Transient simulation of lossy interconnects based on the recursive convolution formulation (250 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Electronic engineering, Routing, Algorithm, Mathematical optimization and Topology. His work deals with themes such as Electronic circuit, Interconnection, Nonlinear system and Transmission line, which intersect with Electronic engineering. Ernest S. Kuh combines subjects such as Network topology, Physical design, Topology and Parallel computing with his study of Routing.

His studies in Algorithm integrate themes in fields like Digital electronics and Linear equation. His Mathematical optimization research integrates issues from Graph theory and Chip. Ernest S. Kuh has included themes like Sensitivity, Method of moments and Voltage in his Topology study.

He most often published in these fields:

• Electronic engineering (37.34%)
• Routing (27.85%)
• Algorithm (25.32%)

What were the highlights of his more recent work (between 1996-2011)?

• Electronic engineering (37.34%)
• Algorithm (25.32%)
• Interconnection (12.03%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Electronic engineering, Algorithm, Interconnection, Topology and Mathematical optimization. He interconnects Electronic circuit, Electric power transmission and Transmission line in the investigation of issues within Electronic engineering. His study in Algorithm is interdisciplinary in nature, drawing from both Transformation, Routing, Network analysis and Parallel computing.

His studies deal with areas such as Physical design, Representation, Chip and Standard cell as well as Interconnection. His biological study spans a wide range of topics, including Transistor and Very-large-scale integration. His studies in Mathematical optimization integrate themes in fields like Function and Integrated circuit layout.

Between 1996 and 2011, his most popular works were:

• Passive multipoint moment matching model order reduction algorithm on multiport distributed interconnect networks (150 citations)
• Sequence-pair based placement method for hard/soft/pre-placed modules (85 citations)
• On projection-based algorithms for model-order reduction of interconnects (79 citations)

In his most recent research, the most cited papers focused on:

• Mathematical analysis
• Electrical engineering
• Algorithm

Ernest S. Kuh mainly investigates Algorithm, Electronic engineering, Matching, Model order reduction and Mathematical optimization. His work deals with themes such as Routing, Representation and Parallel computing, which intersect with Algorithm. His Routing research incorporates themes from Standard cell, Steiner tree problem, Gate array and Router.

His research in Electronic engineering intersects with topics in Distortion and Interconnection. His work carried out in the field of Matching brings together such families of science as Transformation, Admittance, Reduction and Network analysis. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Sequence, Topology and Benchmark.