Marcel R. Ackermann
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
- Artificial Intelligence top 5%
- Data Stream Mining Techniques
- Advanced Clustering Algorithms Research
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
Papers in
-
- Advanced Clustering Algorithms Research 2
- Anomaly Detection Techniques and Applications 2
- Explainable Artificial Intelligence (XAI) 2
- Domain Adaptation and Few-Shot Learning 1
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- Facility Location and Emergency Management 5
- Co-authors
- Christian Sohler (4 shared papers)Johannes Blömer (5 shared papers)Marcus Märtens (1 shared paper)Christiane Lammersen (1 shared paper)Klaus‐Robert Müller (2 shared papers)Sören Becker (1 shared paper)Wojciech Samek (1 shared paper)Sebastian Lapuschkin (1 shared paper)
- Journals
- Algorithmica (1 paper)Journal of the Franklin Institute (1 paper)ACM Transactions on Algorithms (1 paper)ACM Journal of Experimental Algorithmics (1 paper)DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (1 paper)
- Partner nations
- GermanySouth KoreaUnited States
In The Last Decade
Marcel R. Ackermann
9 papers receiving 310 citations
Peers
Comparison fields: 5 of 83
- Signal Processing 114
- Artificial Intelligence 218
- Computer Vision and Pattern Recognition 59
- Computer Graphics and Computer-Aided Design 8
- Statistical and Nonlinear Physics 26
Countries citing papers authored by Marcel R. Ackermann
This map shows the geographic impact of Marcel R. Ackermann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcel R. Ackermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel R. Ackermann more than expected).
Fields of papers citing papers by Marcel R. Ackermann
This network shows the impact of papers produced by Marcel R. Ackermann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcel R. Ackermann. The network helps show where Marcel R. Ackermann may publish in the future.
Co-authors
The 12 scholars most cited alongside Marcel R. Ackermann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 179 | |
| 2 | 2012 | 71 | |
| 3 | 2023 | 30 | |
| 4 | 2010 | 21 | |
| 5 | 2009 | 14 | |
| 6 | Explanations can be manipulated and geometry is to blame | 2019 | 10 |
| 7 | 2009 | 6 | |
| 8 | Hardness and Non-Approximability of Bregman Clustering Problems. | 2011 | 3 |
| 9 | 2011 | 1 | |
| 10 | 2023 | 0 |
About Marcel R. Ackermann
Marcel R. Ackermann is a scholar working on Artificial Intelligence, Organizational Behavior and Human Resource Management, Ocean Engineering, Signal Processing and Applied Mathematics, having authored 10 papers that have together received 335 indexed citations. Recurring topics across this work include Facility Location and Emergency Management (5 papers), Automated Road and Building Extraction (3 papers), Point processes and geometric inequalities (2 papers), Advanced Clustering Algorithms Research (2 papers), Anomaly Detection Techniques and Applications (2 papers), Data Management and Algorithms (2 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Signal Processing (114 citations), Artificial Intelligence (218 citations), Computer Vision and Pattern Recognition (59 citations), Computer Graphics and Computer-Aided Design (8 citations) and Statistical and Nonlinear Physics (26 citations). Marcel R. Ackermann has collaborated with scholars based in Germany, South Korea and United States. Frequent co-authors include Christian Sohler, Johannes Blömer, Marcus Märtens, Christiane Lammersen, Klaus‐Robert Müller, Sören Becker, Wojciech Samek, Sebastian Lapuschkin, Christopher J. Anders and Pan Kessel. Their work appears in journals such as Algorithmica, Journal of the Franklin Institute, ACM Transactions on Algorithms, ACM Journal of Experimental Algorithmics and DROPS (Schloss Dagstuhl – Leibniz Center for Informatics).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.