Edward De Brouwer

806 total citations
10 papers, 51 citations indexed

About

Edward De Brouwer is a scholar working on Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics. According to data from OpenAlex, Edward De Brouwer has authored 10 papers receiving a total of 51 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Signal Processing and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Edward De Brouwer's work include Machine Learning in Healthcare (2 papers), Time Series Analysis and Forecasting (2 papers) and Gaussian Processes and Bayesian Inference (2 papers). Edward De Brouwer is often cited by papers focused on Machine Learning in Healthcare (2 papers), Time Series Analysis and Forecasting (2 papers) and Gaussian Processes and Bayesian Inference (2 papers). Edward De Brouwer collaborates with scholars based in Belgium and United States. Edward De Brouwer's co-authors include Yves Moreau, Ádám Arany, Jaak Simm, Boumediene Hamzi, Jong‐Hyeon Lee, Houman Owhadi, Liesbet M. Peeters, Lotte Geys, Tina Parciak and Zeshan Hussain and has published in prestigious journals such as Scientific Reports, Physica D Nonlinear Phenomena and npj Digital Medicine.

In The Last Decade

Edward De Brouwer

10 papers receiving 48 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Edward De Brouwer Belgium	5	34	15	8	7	4	10	51
Konstantina Palla United Kingdom	5	39 1.1×	9 0.6×	3 0.4×	9 1.3×	15 3.8×	12	79
Vaishnavh Nagarajan United States	4	26 0.8×	6 0.4×	3 0.4×	11 1.6×	3 0.8×	7	44
Behrooz Ghorbani United States	4	47 1.4×	11 0.7×	2 0.3×	18 2.6×	3 0.8×	6	57
Theodor Misiakiewicz United States	5	37 1.1×	10 0.7×	2 0.3×	14 2.0×	1 0.3×	7	60
Jaesik Yoon Netherlands	3	73 2.1×	5 0.3×	5 0.6×	36 5.1×	2 0.5×	5	86
Gary Bécigneul Switzerland	5	47 1.4×	7 0.5×	2 0.3×	22 3.1×	7 1.8×	8	63
Victor Gabillon France	4	22 0.6×	4 0.3×	3 0.4×	10 1.4×	4 1.0×	5	40
Thierry Brouard France	6	38 1.1×	11 0.7×	12 1.5×	53 7.6×	4 1.0×	15	81
Colin Wei United States	4	63 1.9×	8 0.5×	4 0.5×	28 4.0×		8	72
Hansheng Ren China	3	20 0.6×	5 0.3×	6 0.8×	32 4.6×	5 1.3×	4	48

Countries citing papers authored by Edward De Brouwer

Since Specialization

Citations

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

Fields of papers citing papers by Edward De Brouwer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edward De Brouwer. 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 Edward De Brouwer. The network helps show where Edward De Brouwer may publish in the future.

Co-authorship network of co-authors of Edward De Brouwer

This figure shows the co-authorship network connecting the top 25 collaborators of Edward De Brouwer. A scholar is included among the top collaborators of Edward De Brouwer 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 Edward De Brouwer. Edward De Brouwer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Sun, Xingzhi, et al.. (2025). Deep learning unlocks the true potential of organ donation after circulatory death with accurate prediction of time-to-death. Scientific Reports. 15(1). 13565–13565. 1 indexed citations

Peeters, Liesbet M., et al.. (2024). Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study. JMIR Formative Research. 8. e55496–e55496. 2 indexed citations

Hussain, Zeshan, Edward De Brouwer, Neeraj Gupta, et al.. (2024). Joint AI-driven event prediction and longitudinal modeling in newly diagnosed and relapsed multiple myeloma. npj Digital Medicine. 7(1). 200–200. 4 indexed citations

Brouwer, Edward De, et al.. (2024). Atom-Level Optical Chemical Structure Recognition with Limited Supervision. Lirias (KU Leuven). 17669–17678. 1 indexed citations

Brouwer, Edward De, et al.. (2023). The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research. JMIR Medical Informatics. 11. e48030–e48030. 4 indexed citations

Lee, Jong‐Hyeon, Edward De Brouwer, Boumediene Hamzi, & Houman Owhadi. (2022). Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series. Physica D Nonlinear Phenomena. 443. 133546–133546. 10 indexed citations

Brouwer, Edward De, Murat Akand, Frank Van der Aa, et al.. (2022). Augmenting THerapeutic Effectiveness Through Novel Analytics (ATHENA) – A Public and Private Partnership Project Funded by the Flemish Government (VLAIO). Studies in health technology and informatics. 294. 829–833. 2 indexed citations

Brouwer, Edward De, Ádám Arany, Jaak Simm, & Yves Moreau. (2021). Latent Convergent Cross Mapping. Lirias (KU Leuven). 4 indexed citations

Brouwer, Edward De, Ádám Arany, Jaak Simm, & Yves Moreau. (2020). Inferring Causal Dependencies between Chaotic Dynamical Systems from Sporadic Time Series. 1 indexed citations

10.

Brouwer, Edward De, Jaak Simm, Ádám Arany, & Yves Moreau. (2019). GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series. Lirias. 32. 7377–7388. 22 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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