H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 73 Citations 19,828 267 World Ranking 656 National Ranking 395

Research.com Recognitions

Awards & Achievements

1996 - IEEE Fellow For contributions to logic synthesis and computer-aided design; specifically for the development of algorithms for the optimization of area, delay, testability, and power of digital circuits.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Operating system
  • Programming language

Kurt Keutzer focuses on Artificial intelligence, Algorithm, Theoretical computer science, Electronic engineering and Parallel computing. His Artificial intelligence research is multidisciplinary, incorporating elements of Computer vision and Pattern recognition. His work on Hessian matrix expands to the thematically related Algorithm.

Many of his research projects under Theoretical computer science are closely connected to Automatic variable, Addressing mode and Memory address register with Automatic variable, Addressing mode and Memory address register, tying the diverse disciplines of science together. The concepts of his Electronic engineering study are interwoven with issues in Integrated circuit layout and Interconnection. His study in Parallel computing is interdisciplinary in nature, drawing from both Iterative method and Code generation.

His most cited work include:

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
  • DAGON: Technology Binding and Local Optimization by DAG Matching (471 citations)
  • Estimation of average switching activity in combinational and sequential circuits (438 citations)

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

His primary areas of study are Artificial intelligence, Algorithm, Artificial neural network, Parallel computing and Computer architecture. While the research belongs to areas of Artificial intelligence, he spends his time largely on the problem of Pattern recognition, intersecting his research to questions surrounding Domain. His Algorithm study also includes fields such as

  • Testability and related Fault,
  • Electronic engineering most often made with reference to Electronic circuit.

His Artificial neural network study combines topics from a wide range of disciplines, such as Computation, Inference and Convolutional neural network. His studies in CUDA and Speedup are all subfields of Parallel computing research. His biological study deals with issues like Combinational logic, which deal with fields such as Logic optimization.

He most often published in these fields:

  • Artificial intelligence (21.26%)
  • Algorithm (18.84%)
  • Artificial neural network (14.98%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (21.26%)
  • Artificial neural network (14.98%)
  • Algorithm (18.84%)

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

Kurt Keutzer focuses on Artificial intelligence, Artificial neural network, Algorithm, Machine learning and Pattern recognition. In the field of Artificial intelligence, his study on Deep learning and Segmentation overlaps with subjects such as Lidar. His work in Deep learning addresses issues such as Computer engineering, which are connected to fields such as Frame rate.

His studies deal with areas such as Residual, Computation, Inference and Speedup as well as Artificial neural network. The Algorithm study combines topics in areas such as Normalization, Robustness, Hessian matrix and Transformer. Kurt Keutzer interconnects Emotion classification, Feature and Similarity in the investigation of issues within Pattern recognition.

Between 2017 and 2021, his most popular works were:

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge (493 citations)
  • FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search (390 citations)
  • SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud (291 citations)

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

  • Artificial intelligence
  • Operating system
  • Programming language

Artificial intelligence, Artificial neural network, Algorithm, Pattern recognition and Segmentation are his primary areas of study. His Artificial intelligence study incorporates themes from Machine learning and Speedup. His work carried out in the field of Speedup brings together such families of science as Theoretical computer science, Frame rate, Adversarial system and Computer engineering.

His research in Artificial neural network intersects with topics in Convolution, Computer hardware, Inference and Residual. His Algorithm study integrates concerns from other disciplines, such as Normalization and Hessian matrix. The study incorporates disciplines such as Domain, Image and Data modeling in addition to Pattern recognition.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

DAGON: Technology Binding and Local Optimization by DAG Matching

K. Keutzer.
design automation conference (1987)

759 Citations

Estimation of average switching activity in combinational and sequential circuits

A. Ghosh;S. Devadas;K. Keutzer;J. White.
design automation conference (1992)

713 Citations

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
Unknown Journal (2018)

685 Citations

Fast support vector machine training and classification on graphics processors

Bryan Catanzaro;Narayanan Sundaram;Kurt Keutzer.
international conference on machine learning (2008)

509 Citations

Addressing the system-on-a-chip interconnect woes through communication-based design

M. Sgroi;M. Sheets;A. Mihal;K. Keutzer.
design automation conference (2001)

491 Citations

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

Bichen Wu;Kurt Keutzer;Xiaoliang Dai;Peizhao Zhang.
computer vision and pattern recognition (2019)

483 Citations

Dense point trajectories by GPU-accelerated large displacement optical flow

Narayanan Sundaram;Thomas Brox;Kurt Keutzer.
european conference on computer vision (2010)

430 Citations

Getting to the bottom of deep submicron

Dennis Sylvester;Kurt Keutzer.
international conference on computer aided design (1998)

385 Citations

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Bichen Wu;Forrest Iandola;Peter H. Jin;Kurt Keutzer.
computer vision and pattern recognition (2017)

381 Citations

Bus encoding to prevent crosstalk delay

Bret Victor;Kurt Keutzer.
international conference on computer aided design (2001)

348 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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