World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
60483
World Ranking
5729
National Ranking
219

Research.com Recognitions

  • 2015 - ACM Distinguished Member

Overview

Jörg Sander is affiliated with the University of Alberta in Canada and has contributed extensively to research in computer science and engineering. Their work predominantly focuses on artificial intelligence, with particular attention to anomaly detection techniques and applications.

The scientist has a strong research presence in several interconnected fields and subfields. The main areas of study include:

  • Computer Science
  • Engineering

Within these broader categories, more specific subfields addressed in their work are:

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Molecular Biology
  • Computer Vision and Pattern Recognition
  • Epidemiology

The thematic concentration of Jörg Sander's research centers around:

  • Anomaly Detection Techniques and Applications
  • Water Systems and Optimization
  • Data-Driven Disease Surveillance
  • Advanced Clustering Algorithms Research
  • Imbalanced Data Classification Techniques
  • Bayesian Methods and Mixture Models
  • Data Management and Algorithms

Jörg Sander has published in several key journals and conferences, demonstrating engagement with a mixture of data mining, knowledge discovery, and bioinformatics venues. Frequent publication venues include:

  • Data Mining and Knowledge Discovery
  • arXiv (Cornell University)
  • ACM Transactions on Knowledge Discovery from Data
  • 2022 IEEE 38th International Conference on Data Engineering (ICDE)
  • Briefings in Bioinformatics

Their recent papers illustrate a strong focus on outlier detection, evaluation methods, and computational approaches. Selected recent publications are:

  • Internal Evaluation of Unsupervised Outlier Detection, 2020, ACM Transactions on Knowledge Discovery from Data
  • On the evaluation of outlier detection and one-class classification: a comparative study of algorithms, model selection, and ensembles, 2023, Data Mining and Knowledge Discovery
  • CORE-SG: Efficient Computation of Multiple MSTs for Density-Based Methods, 2022, 2022 IEEE 38th International Conference on Data Engineering (ICDE)
  • Potential of dissimilarity measure-based computation of protein thermal stability data for determining protein interactions, 2023, Briefings in Bioinformatics
  • Efficient outlier detection in numerical and categorical data, 2025, Data Mining and Knowledge Discovery

Collaborations have been an integral part of their research, with frequent coauthors including:

  • Ricardo J. G. B. Campello
  • Arthur Zimek
  • Henrique O. Marques
  • Murilo Coelho Naldi
  • Bob D. de Vos

In recognition of their contributions to the field, Jörg Sander was awarded the ACM Distinguished Member honor in 2015.

Best Publications

  • A density-based algorithm for discovering clusters in large spatial Databases with Noise

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Xiaowei Xu

  • LOF: identifying density-based local outliers

    Markus M. Breunig;Hans-Peter Kriegel;Raymond T. Ng;Jörg Sander

  • OPTICS: ordering points to identify the clustering structure

    Mihael Ankerst;Markus M. Breunig;Hans-Peter Kriegel;Jörg Sander

  • DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

    Erich Schubert;Jörg Sander;Martin Ester;Hans Peter Kriegel

  • Density-Based Clustering Based on Hierarchical Density Estimates

    Ricardo J. G. B. Campello;Davoud Moulavi;Joerg Sander

  • Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

    Jörg Sander;Martin Ester;Hans-Peter Kriegel;Xiaowei Xu

  • A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Xiaowei Xu

  • Density-based clustering

    Hans Peter Kriegel;Peer Kröger;Jörg Sander;Arthur Zimek

  • Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

    Ricardo J. G. B. Campello;Davoud Moulavi;Arthur Zimek;Jörg Sander

  • On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study

    Guilherme O. Campos;Arthur Zimek;Jörg Sander;Ricardo J. Campello

  • Incremental Clustering for Mining in a Data Warehousing Environment

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Michael Wimmer

  • A distribution-based clustering algorithm for mining in large spatial databases

    Xiaowei Xu;M. Ester;H.-P. Kriegel;J. Sander

  • Spatial Data Mining: A Database Approach

    Martin Ester;Hans-Peter Kriegel;Jörg Sander

  • Knowledge Discovery in Databases - Techniken und Anwendungen

    Martin Ester;Jörg Sander

  • Ensembles for unsupervised outlier detection: challenges and research questions a position paper

    Arthur Zimek;Ricardo J.G.B. Campello;Jörg Sander

  • OPTICS-OF: Identifying Local Outliers

    Markus M. Breunig;Hans-Peter Kriegel;Raymond T. Ng;Jörg Sander

  • Density-based clustering validation

    Davoud Moulavi;Pablo A. Jaskowiak;Pablo A. Jaskowiak;Ricardo J.G.B. Campello;Arthur Zimek

  • Independent quantization: an index compression technique for high-dimensional data spaces

    S. Berchtold;C. Bohm;H.V. Jagadish;H.-P. Kriegel

  • Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support

    Martin Ester;Alexander Frommelt;Hans-Peter Kriegel;Jöorg Sander

  • Subsampling for efficient and effective unsupervised outlier detection ensembles

    Arthur Zimek;Matthew Gaudet;Ricardo J.G.B. Campello;Jörg Sander

Frequent Co-Authors

Hans-Peter Kriegel
Hans-Peter Kriegel Ludwig-Maximilians-Universität München
Martin Ester
Martin Ester Simon Fraser University
Ricardo J. G. B. Campello
Ricardo J. G. B. Campello University of Southern Denmark
Arthur Zimek
Arthur Zimek University of Southern Denmark
Xiaowei Xu
Xiaowei Xu University of Arkansas at Little Rock
Raymond T. Ng
Raymond T. Ng University of British Columbia
Russell Greiner
Russell Greiner University of Alberta
Peer Kröger
Peer Kröger Kiel University
Mark Schmidt
Mark Schmidt University of British Columbia
Steven J.M. Jones
Steven J.M. Jones University of British Columbia

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