2026 Jörg Sander: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	49	5730	5567	218	207	109	60483

Jörg Sander publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Jörg Sander sits on this spectrum.

32 publications 991+

This scientist: 109 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Jörg Sander D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Jörg Sander sits on this spectrum.

30 D-Index 131+

This scientist: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

27839
Citations
LOF: identifying density-based local outliers

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

7807
Citations
OPTICS: ordering points to identify the clustering structure

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

5945
Citations
DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

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

2563
Citations
Density-Based Clustering Based on Hierarchical Density Estimates

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

2367
Citations
Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

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

2072
Citations
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

1551
Citations
Density-based clustering

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

1085
Citations
Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

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

875
Citations
On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study

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

793
Citations
Incremental Clustering for Mining in a Data Warehousing Environment

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

658
Citations
A distribution-based clustering algorithm for mining in large spatial databases

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

555
Citations
Spatial Data Mining: A Database Approach

Martin Ester;Hans-Peter Kriegel;Jörg Sander

447
Citations
Knowledge Discovery in Databases - Techniken und Anwendungen

Martin Ester;Jörg Sander

359
Citations
Ensembles for unsupervised outlier detection: challenges and research questions a position paper

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

346
Citations
OPTICS-OF: Identifying Local Outliers

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

324
Citations
Density-based clustering validation

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

288
Citations
Independent quantization: an index compression technique for high-dimensional data spaces

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

287
Citations
Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support

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

240
Citations
Subsampling for efficient and effective unsupervised outlier detection ensembles

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

234
Citations

Frequent Co-Authors

Hans-Peter Kriegel Ludwig-Maximilians-Universität München

Martin Ester Simon Fraser University

Ricardo J. G. B. Campello University of Southern Denmark

Arthur Zimek University of Southern Denmark

Xiaowei Xu University of Arkansas at Little Rock

Raymond T. Ng University of British Columbia

Russell Greiner University of Alberta

Peer Kröger Kiel University

Mark Schmidt University of British Columbia

Steven J.M. Jones University of British Columbia

External Links

Personal website of Jörg Sander Google Scholar page

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