Geert Gins

821 total citations
34 papers, 640 citations indexed

About

Geert Gins is a scholar working on Control and Systems Engineering, Mechanical Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Geert Gins has authored 34 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Control and Systems Engineering, 13 papers in Mechanical Engineering and 12 papers in Statistics, Probability and Uncertainty. Recurrent topics in Geert Gins's work include Fault Detection and Control Systems (23 papers), Mineral Processing and Grinding (13 papers) and Advanced Statistical Process Monitoring (11 papers). Geert Gins is often cited by papers focused on Fault Detection and Control Systems (23 papers), Mineral Processing and Grinding (13 papers) and Advanced Statistical Process Monitoring (11 papers). Geert Gins collaborates with scholars based in Belgium, Portugal and Netherlands. Geert Gins's co-authors include Marco S. Reis, Jan Van Impe, Ilse Smets, Tiago J. Rato, Rob Van den Broeck, Jules B. van Lier, J.H.J.M. van der Graaf, Jan Degrève, Lise Appels and Joost Lauwers and has published in prestigious journals such as Environmental Science & Technology, Journal of Membrane Science and Industrial & Engineering Chemistry Research.

In The Last Decade

Geert Gins

30 papers receiving 629 citations

Peers

Geert Gins
Sergio Valle‐Cervantes Mexico
In‐Beum Lee South Korea
Hongyang Yu China
César de Prada Spain
M.J. Fuente Spain
Mika Liukkonen Finland
Yiqi Liu China
G.I. Sainz-Palmero Spain
Sandip Kumar Lahiri India
Zhiyuan Wang Singapore
Sergio Valle‐Cervantes Mexico
Geert Gins
Citations per year, relative to Geert Gins Geert Gins (= 1×) peers Sergio Valle‐Cervantes

Countries citing papers authored by Geert Gins

Since Specialization
Citations

This map shows the geographic impact of Geert Gins'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 Geert Gins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geert Gins more than expected).

Fields of papers citing papers by Geert Gins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geert Gins. 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 Geert Gins. The network helps show where Geert Gins may publish in the future.

Co-authorship network of co-authors of Geert Gins

This figure shows the co-authorship network connecting the top 25 collaborators of Geert Gins. A scholar is included among the top collaborators of Geert Gins based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Geert Gins. Geert Gins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Reis, Marco S., Geert Gins, & Tiago J. Rato. (2019). Incorporation of process-specific structure in statistical process monitoring: A review. Journal of Quality Technology. 51(4). 407–421. 26 indexed citations
2.
Gins, Geert, et al.. (2016). Bioflocculation and Activated Sludge Separation: A PLS Case Study. IFAC-PapersOnLine. 49(7). 1151–1156. 1 indexed citations
3.
Gins, Geert, et al.. (2015). Fault Identification in Batch Processes Using Process Data or Contribution Plots: A Comparative Study. 8. 1283–1288. 2 indexed citations
4.
5.
Impe, Jan Van & Geert Gins. (2015). An extensive reference dataset for fault detection and identification in batch processes. Chemometrics and Intelligent Laboratory Systems. 148. 20–31. 27 indexed citations
6.
Gins, Geert, et al.. (2014). The RAYMOND simulation package — Generating RAYpresentative MONitoring Data to design advanced process monitoring and control algorithms. Computers & Chemical Engineering. 69. 108–118. 10 indexed citations
7.
Vermeulen, An, Mieke Uyttendaele, Geert Gins, et al.. (2013). Predictive models to support manufacturers of processed meat in their compliance with EU regulation 2073/2005. Ghent University Academic Bibliography (Ghent University). 2 indexed citations
8.
Gins, Geert, et al.. (2013). Quality assessment of a variance estimator for Partial Least Squares prediction of batch-end quality. Computers & Chemical Engineering. 52. 230–239. 10 indexed citations
9.
Gins, Geert, et al.. (2012). Hybrid Derivative Dynamic Time Warping for Online Industrial Batch-End Quality Estimation. Industrial & Engineering Chemistry Research. 51(17). 6071–6084. 21 indexed citations
10.
Gins, Geert, et al.. (2012). Extending discrete batch-end quality optimization to online implementation. IFAC Proceedings Volumes. 45(15). 910–915. 1 indexed citations
11.
Gins, Geert, et al.. (2012). Online batch fault diagnosis with Least Squares Support Vector Machines. IFAC Proceedings Volumes. 45(20). 432–437. 1 indexed citations
12.
Appels, Lise, Joost Lauwers, Geert Gins, et al.. (2011). Parameter Identification and Modeling of the Biochemical Methane Potential of Waste Activated Sludge. Environmental Science & Technology. 45(9). 4173–4178. 36 indexed citations
13.
Dewil, Raf, Joost Lauwers, Lise Appels, et al.. (2011). Anaerobic digestion of biomass and waste: current trends in mathematical modeling. IFAC Proceedings Volumes. 44(1). 5024–5033. 6 indexed citations
14.
Gins, Geert, et al.. (2009). Online batch-end quality estimation: does laziness pay off. IFAC Proceedings Volumes. 42(8). 1246–1251. 3 indexed citations
15.
Gins, Geert, Ilse Smets, & Jan Van Impe. (2007). Efficient Tracking of the Dominant Eigenspace of a Normalized Kernel Matrix. Neural Computation. 20(2). 523–554. 1 indexed citations
16.
Gins, Geert, Ilse Smets, & Jan Van Impe. (2006). Efficient tracking of the dominant eigenspace of a normalized kernel matrix, part I: the algorithm. 1 indexed citations
17.
Gins, Geert, Ilse Smets, & Jan Van Impe. (2006). Efficient tracking of the dominant eigenspace of a normalized kernel matrix, part II: performance assessment. 1 indexed citations
18.
Gins, Geert, Ilse Smets, R. Jenné, & Jan Van Impe. (2005). ACTIVATED SLUDGE IMAGE ANALYSIS DATA CLASSIFICATION: AN LS-SVM APPROACH. IFAC Proceedings Volumes. 38(1). 37–42. 4 indexed citations
19.
Jenné, R., et al.. (2004). Developing an early warning tool for filamentous bulking problems based on image analysis. 221–228. 2 indexed citations
20.
Banadda, E. N., et al.. (2004). Identification and Modeling of the Sludge Volume Index by Exploiting Image Analysis Information. IFAC Proceedings Volumes. 37(3). 85–90. 2 indexed citations

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.

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