Michiel de Jong

522 total citations · 1 hit paper
11 papers, 215 citations indexed

About

Michiel de Jong is a scholar working on Artificial Intelligence, Demography and Social Psychology. According to data from OpenAlex, Michiel de Jong has authored 11 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Demography and 2 papers in Social Psychology. Recurrent topics in Michiel de Jong's work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Technology Use by Older Adults (3 papers). Michiel de Jong is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Technology Use by Older Adults (3 papers). Michiel de Jong collaborates with scholars based in United States, Italy and Netherlands. Michiel de Jong's co-authors include Joshua Ainslie, Yury Zemlyanskiy, James Lee-Thorp, Vera Stara, Mirko Di Rosa, Elisa Felici, Lorena Rossi, Vanessa Evers, Marcel Heerink and Fei Sha and has published in prestigious journals such as International Journal of Environmental Research and Public Health, ACM SIGPLAN Notices and JMIR mhealth and uhealth.

In The Last Decade

Michiel de Jong

11 papers receiving 205 citations

Hit Papers

GQA: Training Generalized Multi-Query Transformer Models ... 2023 2026 2024 2025 2023 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michiel de Jong United States 7 116 29 23 20 16 11 215
Michalis Foukarakis Greece 10 47 0.4× 60 2.1× 21 0.9× 29 1.4× 4 0.3× 18 194
Rina Azoulay Israel 6 114 1.0× 15 0.5× 4 0.2× 34 1.7× 20 1.3× 24 226
Mor Vered Australia 8 135 1.2× 26 0.9× 13 0.6× 2 0.1× 7 0.4× 24 219
Klaus-Peter Engelbrecht Germany 10 160 1.4× 81 2.8× 13 0.6× 20 1.0× 37 2.3× 32 297
Liyakathunisa Syed Saudi Arabia 8 67 0.6× 57 2.0× 11 0.5× 64 3.2× 43 2.7× 22 243
Syin Chan Singapore 9 182 1.6× 61 2.1× 10 0.4× 48 2.4× 47 2.9× 29 357
Shiwali Mohan United States 10 149 1.3× 40 1.4× 3 0.1× 12 0.6× 11 0.7× 28 277
Izabela Stefaniak Poland 4 136 1.2× 34 1.2× 11 0.6× 27 1.7× 12 223
Ivan Donadello Italy 10 181 1.6× 32 1.1× 2 0.1× 3 0.1× 19 1.2× 22 261
Robert Templeman United States 7 92 0.8× 152 5.2× 8 0.3× 35 1.8× 85 5.3× 8 378

Countries citing papers authored by Michiel de Jong

Since Specialization
Citations

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

Fields of papers citing papers by Michiel de Jong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michiel de Jong. 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 Michiel de Jong. The network helps show where Michiel de Jong may publish in the future.

Co-authorship network of co-authors of Michiel de Jong

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

All Works

11 of 11 papers shown
1.
Ainslie, Joshua, et al.. (2023). GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints. 4895–4901. 124 indexed citations breakdown →
2.
Chen, Wenhu, et al.. (2023). Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering. 1597–1610. 3 indexed citations
3.
Jong, Michiel de, Yury Zemlyanskiy, Joshua Ainslie, et al.. (2023). FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. 11534–11547. 5 indexed citations
4.
Ainslie, Joshua, Michiel de Jong, Santiago Ontañón, et al.. (2023). CoLT5: Faster Long-Range Transformers with Conditional Computation. 5085–5100. 18 indexed citations
5.
Stara, Vera, et al.. (2021). Toward the Integration of Technology-Based Interventions in the Care Pathway for People with Dementia: A Cross-National Study. International Journal of Environmental Research and Public Health. 18(19). 10405–10405. 8 indexed citations
6.
Zemlyanskiy, Yury, Joshua Ainslie, Michiel de Jong, et al.. (2021). ReadTwice: Reading Very Large Documents with Memories. 5189–5195. 7 indexed citations
8.
Jong, Michiel de, Marike Hettinga, Vera Stara, Vanessa Evers, & Jamy Li. (2019). Eldertainment or functional necessity?. University of Twente Research Information. 41–44. 3 indexed citations
9.
Jong, Michiel de, et al.. (2018). Towards a Robust Interactive and Learning Social Robot. 883–891. 12 indexed citations
10.
Jong, Michiel de, et al.. (2018). Users requirements in the design of a virtual agent for patients with dementia and their caregivers. University of Twente Research Information. 136–141. 13 indexed citations
11.
Jong, Michiel de & Chris Hankin. (1982). Structured data flow programming. ACM SIGPLAN Notices. 17(8). 18–27. 3 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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