World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
5314
World Ranking
12122
National Ranking
58

Overview

Ira Assent is a researcher affiliated with Aarhus University in Denmark, specializing in computer science with a focus on artificial intelligence and related subfields. Their work covers a range of topics including advanced clustering algorithms, data mining applications, semantic web technologies, remote sensing in agriculture, explainable artificial intelligence, precipitation measurement, and data management strategies.

Their publication record includes contributions to several peer-reviewed venues. Notable recent papers include:

  • TimeMatch: Unsupervised cross-region adaptation by temporal shift estimation, 2022, ISPRS Journal of Photogrammetry and Remote Sensing
  • Incremental Density-Based Clustering on Multicore Processors, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • GLEAN: Generalized-Deduplication-Enabled Approximate Edge Analytics, 2022, IEEE Internet of Things Journal
  • TextBenDS: a Generic Textual Data Benchmark for Distributed Systems, 2020, Information Systems Frontiers
  • From Demo to Design in Teaching Machine Learning, 2022, 2022 ACM Conference on Fairness, Accountability, and Transparency

Assent has collaborated frequently with a number of researchers, including:

  • Joachim Nyborg
  • Davide Mottin
  • Andrew Draganov
  • Jakob Rødsgaard Jørgensen
  • Hanno Scharr

Their research is often published in venues such as arXiv (Cornell University), Research Portal (King's College London), Machine Learning journals, IEEE conferences, and ISPRS journals. This diversity highlights the interdisciplinary nature of their work spanning multiple domains related to computer science and artificial intelligence.

Within the field of computer science, they focus extensively on the following subfields:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Atmospheric Science
  • Signal Processing
  • Information Systems

Key topics addressed in their publications include:

  • Advanced Clustering Algorithms Research
  • Data Mining Algorithms and Applications
  • Semantic Web and Ontologies
  • Remote Sensing in Agriculture
  • Explainable Artificial Intelligence (XAI)
  • Precipitation Measurement and Analysis
  • Data Management and Algorithms

Best Publications

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

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

  • Evaluating Clustering in Subspace Projections of High Dimensional Data

    Emmanuel Müller;Stephan Günnemann;Ira Assent;Thomas Seidl

  • Evaluating clustering in subspace projections of high dimensional data

    Emmanuel Müller;Stephan Günnemann;Ira Assent;Thomas Seidl

  • The ClusTree: indexing micro-clusters for anytime stream mining

    Philipp Kranen;Ira Assent;Corinna Baldauf;Thomas Seidl

  • Clustering high dimensional data

    Ira Assent

  • DUSC: Dimensionality Unbiased Subspace Clustering

    I. Assent;R. Krieger;E. Muller;T. Seidl

  • Clicks: An effective algorithm for mining subspace clusters in categorical datasets

    Mohammed J. Zaki;Markus Peters;Ira Assent;Thomas Seidl

  • INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy

    I. Assent;R. Krieger;E. Muller;T. Seidl

  • Explaining Outliers by Subspace Separability

    Barbora Micenkova;Xuan-Hong Dang;Ira Assent;Raymond T. Ng

  • AnyOut: anytime outlier detection on streaming data

    Ira Assent;Philipp Kranen;Corinna Baldauf;Thomas Seidl

  • Outsourced Similarity Search on Metric Data Assets

    Man Lung Yiu;I. Assent;C. S. Jensen;P. Kalnis

  • The TS-tree: efficient time series search and retrieval

    Ira Assent;Ralph Krieger;Farzad Afschari;Thomas Seidl

  • OutRank: ranking outliers in high dimensional data

    E. Muller;I. Assent;U. Steinhausen;T. Seidl

  • Discriminative features for identifying and interpreting outliers

    Xuan Hong Dang;Ira Assent;Raymond T. Ng;Arthur Zimek

  • Outlier Ranking via Subspace Analysis in Multiple Views of the Data

    Emmanuel Muller;Ira Assent;Patricia Iglesias;Yvonne Mulle

  • Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data

    Emmanuel Müller;Ira Assent;Stephan Günnemann;Ralph Krieger

  • Anticipatory DTW for efficient similarity search in time series databases

    Ira Assent;Marc Wichterich;Ralph Krieger;Hardy Kremer

  • Self-Adaptive Anytime Stream Clustering

    Philipp Kranen;Ira Assent;Corinna Baldauf;Thomas Seidl

  • Approximation Techniques for Indexing the Earth Mover’s Distance in Multimedia Databases

    I. Assent;A. Wenning;T. Seidl

  • VISA: visual subspace clustering analysis

    Ira Assent;Ralph Krieger;Emmanuel Müller;Thomas Seidl

  • Local outlier detection with interpretation

    Xuan Hong Dang;Barbora Micenková;Ira Assent;Raymond T. Ng

Frequent Co-Authors

Thomas Seidl
Thomas Seidl Ludwig-Maximilians-Universität München
Stephan Günnemann
Stephan Günnemann Technical University of Munich
Arthur Zimek
Arthur Zimek University of Southern Denmark
Carlotta Domeniconi
Carlotta Domeniconi George Mason University
Raymond T. Ng
Raymond T. Ng University of British Columbia
Nikos Mamoulis
Nikos Mamoulis University of Ioannina
Torben Bach Pedersen
Torben Bach Pedersen Aalborg University
Aristides Gionis
Aristides Gionis Royal Institute of Technology
Eyke Hüllermeier
Eyke Hüllermeier Ludwig-Maximilians-Universität München
Sihem Amer-Yahia
Sihem Amer-Yahia Grenoble Alpes University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees in Computer Science opens a world of flexible education and diverse career paths. From fast-track programs like 1 year associate degree programs online to advanced studies, there’s a program to fit almost every goal and schedule.

Cost is a vital consideration for many students. Thankfully, there are many cheapest online degrees available, making it easier to earn a respected qualification without accumulating overwhelming debt.

For those worried about academic requirements, several accredited online graduate schools with low gpa requirements can help you continue your studies, even if your previous academic record isn’t perfect.

If you’re considering an advanced credential, Computer Science consistently appears among the most in demand masters degrees. These pathways can lead to high-paying roles and future-proof your career in tech.

Best Scientists Citing Ira Assent

Trending Scientists

Recently Published Articles