World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
5921
World Ranking
12979
National Ranking
389

Overview

Kate A. Smith is affiliated with Monash University in Australia. Their research primarily spans the fields of Computer Science and Engineering, with notable focus on Artificial Intelligence, Industrial and Manufacturing Engineering, Computational Theory and Mathematics, Civil and Structural Engineering, and Management Science and Operations Research.

Their body of work covers several specific topics including:

  • Machine Learning and Data Classification
  • Water Systems and Optimization
  • Advanced Multi-Objective Optimization Algorithms
  • Anomaly Detection Techniques and Applications
  • Data Stream Mining Techniques
  • Urban Stormwater Management Solutions
  • Machine Learning and Algorithms

Frequent co-authors collaborating with Kate A. Smith include:

  • Mario Andrés Muñoz
  • Shuming Liu
  • Ana Carolina Lorena
  • Tim D. Fletcher
  • Nicolau Andrés-Thió

Smith has published extensively in several academic venues, with repeated contributions to:

  • arXiv (Cornell University)
  • Computers & Operations Research
  • INFORMS Journal on Computing
  • European Journal of Operational Research
  • Journal of Water Resources Planning and Management

Among recent papers, Smith's research includes:

  • A transformation technique for the clustered generalized traveling salesman problem with applications to logistics (2020, European Journal of Operational Research)
  • Predicting solutions of large-scale optimization problems via machine learning: A case study in blood supply chain management (2020, Computers & Operations Research)
  • Leakage Detection in Water Distribution Systems Based on Time-Frequency Convolutional Neural Network (2020, Journal of Water Resources Planning and Management)
  • Burst Detection in District Metering Areas Using Deep Learning Method (2020, Journal of Water Resources Planning and Management)
  • China's enhanced urban wastewater treatment increases greenhouse gas emissions and regional inequality (2022, Water Research)

Best Publications

  • Characteristic-Based Clustering for Time Series Data

    Xiaozhe Wang;Kate Smith;Rob Hyndman

  • Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research

    Kate A. Smith

  • On learning algorithm selection for classification

    Shawkat Ali;Kate A. Smith

  • Neural networks in business: techniques and applications for the operations researcher

    Kate A. Smith;Jatinder N.D. Gupta

  • On chaotic simulated annealing

    L. Wang;K. Smith

  • Static and dynamic channel assignment using neural networks

    K. Smith;M. Palaniswami

  • Web page clustering using a self-organizing map of user navigation patterns

    Kate A. Smith;Alan Ng

  • An Analysis of Customer Retention and Insurance Claim Patterns using Data Mining: A Case Study

    Kate A Smith;Robert J Willis;Malcolm Brooks

  • Neural techniques for combinatorial optimization with applications

    K. Smith;M. Palaniswami;M. Krishnamoorthy

  • Neural Networks in Business: Techniques and Applications

    Kate A. Smith;Jatinder N. D. Gupta

  • ODAM: An optimized distributed association rule mining algorithm

    M.Z. Ashrafi;D. Taniar;K. Smith

  • Parallel Fuzzy c-Means Clustering for Large Data Sets

    Terence Kwok;Kate A. Smith;Sebastián Lozano;David Taniar

  • Intelligent web traffic mining and analysis

    Xiaozhe Wang;Ajith Abraham;Kate A. Smith

  • Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework

    T. Kwok;K. A. Smith

  • A unified framework for chaotic neural-network approaches to combinatorial optimization

    T. Kwok;K.A. Smith

  • Hopfield neural networks for timetabling: formulations, methods, and comparative results

    Kate A. Smith;David Abramson;David Duke

  • Neural versus traditional approaches to the location of interacting hub facilities

    Kate Smith;M Krishnamoorthy;Marimuthu Palaniswami

  • Clustering technique for risk classification and prediction of claim costs in the automobile insurance industry

    Ai Cheo Yeo;Kate A. Smith;Robert J. Willis;Malcolm Brooks

  • Manufacturing cell formation using a new self-organizing neural network

    Fernando Guerrero;Sebastian Lozano;Kate A. Smith;David Canca

  • Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem

    Kate Smith;Kate Smith;M. Palaniswami;M. Krishnamoorthy

  • Network and information security: a computational intelligence approach special issue of journal of network and computer applications

    Ajith Abraham;Kate Smith;Ravi Jain;Lakhmi Jain

Frequent Co-Authors

David Taniar
David Taniar Monash University
Sebastián Lozano
Sebastián Lozano University of Seville
Marimuthu Palaniswami
Marimuthu Palaniswami University of Melbourne
Chung-Hsing Yeh
Chung-Hsing Yeh Monash University
Mohan Krishnamoorthy
Mohan Krishnamoorthy University of Queensland
Ajith Abraham
Ajith Abraham Sai University
David Abramson
David Abramson University of Queensland
Lipo Wang
Lipo Wang Nanyang Technological University
Jatinder N. D. Gupta
Jatinder N. D. Gupta University of Alabama in Huntsville
Malin Premaratne
Malin Premaratne Monash University

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