D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 58 Citations 11,864 357 World Ranking 788 National Ranking 48

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Artificial intelligence
  • Programming language

Claudia Eckert mainly investigates Engineering design process, New product development, Artificial intelligence, Machine learning and Product. Her studies deal with areas such as Knowledge management, Design process, Process and Process management as well as Engineering design process. Her New product development research incorporates themes from Product design, Systems engineering, Industrial engineering and Engineering management.

Her biological study spans a wide range of topics, including State and Malware. Her research in Machine learning focuses on subjects like Pattern recognition, which are connected to Detector. Her Product research is multidisciplinary, relying on both Risk analysis and Function.

Her most cited work include:

  • Predicting change propagation in complex design (558 citations)
  • Change and customisation in complex engineering domains (460 citations)
  • Sources of inspiration: a language of design (261 citations)

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

Her primary areas of study are Engineering design process, Process, Systems engineering, Design process and Product. Her Engineering design process study combines topics from a wide range of disciplines, such as Management science, Industrial engineering, Engineering management, Knowledge management and New product development. Claudia Eckert frequently studies issues relating to Process management and Knowledge management.

Her New product development research integrates issues from Product design and Manufacturing engineering. Her Design process study typically links adjacent topics like Process modeling. As part of her studies on Product, she frequently links adjacent subjects like Risk analysis.

She most often published in these fields:

  • Engineering design process (19.01%)
  • Process (12.81%)
  • Systems engineering (12.19%)

What were the highlights of her more recent work (between 2014-2021)?

  • Engineering design process (19.01%)
  • Process (12.81%)
  • New product development (10.33%)

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

Her main research concerns Engineering design process, Process, New product development, Design process and Artificial intelligence. Claudia Eckert combines subjects such as Context, Management science, Engineering management, Terminology and Product with her study of Engineering design process. Her studies in Product integrate themes in fields like Truck and Systems engineering.

Her work in Process tackles topics such as Function which are related to areas like Benchmarking, Reverse engineering and Software engineering. The concepts of her Design process study are interwoven with issues in Key, Engineering ethics, Risk analysis and Product engineering. Her Artificial intelligence study incorporates themes from Machine learning and Malware.

Between 2014 and 2021, her most popular works were:

  • Is Feature Selection Secure against Training Data Poisoning (201 citations)
  • Deep Learning for Classification of Malware System Call Sequences (183 citations)
  • Support vector machines under adversarial label contamination (130 citations)

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

  • Operating system
  • Artificial intelligence
  • Programming language

Claudia Eckert mostly deals with Engineering design process, Artificial intelligence, Malware, Machine learning and Process. Her research integrates issues of Management science, Terminology, Product, Design process and Component in her study of Engineering design process. Her Artificial intelligence research is multidisciplinary, incorporating elements of Diagram, GRASP and Functional decomposition.

The Malware study combines topics in areas such as Executable, Support vector machine, Data structure, Feature selection and Asset. Her Machine learning research incorporates elements of Functional analysis, Training set, Data mining and Product. Her Process research focuses on Resource and how it relates to Empirical research, Decision support system and Knowledge management.

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.

Best Publications

Predicting change propagation in complex design

P. John Clarkson;Caroline Simons;Claudia Eckert.
Journal of Mechanical Design (2001)

864 Citations

Change and customisation in complex engineering domains

Claudia Eckert;P. John Clarkson;Winfried Zanker.
Research in Engineering Design (2004)

692 Citations

Sources of inspiration: a language of design

Claudia Eckert;Martin Stacey.
Design Studies (2000)

485 Citations

Engineering change: an overview and perspective on the literature

T. A. W. Jarratt;T. A. W. Jarratt;C. M. Eckert;N. H. M. Caldwell;P. J. Clarkson.
Research in Engineering Design (2011)

404 Citations

Deep Learning for Classification of Malware System Call Sequences

Bojan Kolosnjaji;Apostolis Zarras;George D. Webster;Claudia Eckert.
australasian joint conference on artificial intelligence (2016)

343 Citations

Design process improvement : a review of current practice

PJ Clarkson;CM Eckert.
(2005)

339 Citations

Change Propagation Analysis in Complex Technical Systems

Monica Giffin;Olivier de Weck;Gergana Bounova;Rene Keller.
Journal of Mechanical Design (2007)

304 Citations

Distributed Attribute-Based Encryption

Sascha Müller;Stefan Katzenbeisser;Claudia Eckert.
international conference on information security and cryptology (2009)

274 Citations

Is negative selection appropriate for anomaly detection

Thomas Stibor;Philipp Mohr;Jonathan Timmis;Claudia Eckert.
genetic and evolutionary computation conference (2005)

231 Citations

Is Feature Selection Secure against Training Data Poisoning

Huang Xiao;Battista Biggio;Gavin Brown;Giorgio Fumera.
international conference on machine learning (2015)

202 Citations

Best Scientists Citing Claudia Eckert

P. John Clarkson

P. John Clarkson

University of Cambridge

Publications: 48

Battista Biggio

Battista Biggio

University of Cagliari

Publications: 28

Tyson R. Browning

Tyson R. Browning

Texas Christian University

Publications: 20

Fabio Roli

Fabio Roli

University of Cagliari

Publications: 18

Kristin L. Wood

Kristin L. Wood

University of Colorado Denver

Publications: 17

Zheng Yan

Zheng Yan

Shanghai Jiao Tong University

Publications: 16

Yoram Reich

Yoram Reich

Tel Aviv University

Publications: 15

Olivier de Weck

Olivier de Weck

MIT

Publications: 15

George Kesidis

George Kesidis

Pennsylvania State University

Publications: 14

Richard de Neufville

Richard de Neufville

MIT

Publications: 14

Dipankar Dasgupta

Dipankar Dasgupta

University of Memphis

Publications: 14

Julie S. Linsey

Julie S. Linsey

Georgia Institute of Technology

Publications: 14

Uwe Aickelin

Uwe Aickelin

University of Melbourne

Publications: 13

Timothy W. Simpson

Timothy W. Simpson

Pennsylvania State University

Publications: 13

Imre J. Rudas

Imre J. Rudas

Óbuda University

Publications: 11

Xiaojin Zhu

Xiaojin Zhu

University of Wisconsin–Madison

Publications: 11

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

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