Jonas Doevenspeck

414 citations
18 papers · 213 · h-index 7

Impact in

Papers in

    • Advanced Memory and Neural Computing 16
    • Ferroelectric and Negative Capacitance Devices 14
    • Semiconductor materials and devices 6
    • Optical Network Technologies 1
    • Fuel Cells and Related Materials 1
    • Machine Learning and ELM 3
    • Neural Networks and Applications 2

Jonas Doevenspeck

18 papers receiving 208 citations

Peers

Jonas Doevenspeck
Comparison fields: 5 of 26
  • Electrical and Electronic Engineering 194
  • Hardware and Architecture 22
  • Artificial Intelligence 49
  • Computer Vision and Pattern Recognition 27
  • Bioengineering 6
Replace Ioannis A. Papistas with:
Ioannis A. Papistas Belgium
Ameya D. Patil United States
Jui-Jen Wu Taiwan
Mohammad Khaleqi Qaleh Jooq Iran
Samuel Spetalnick United States
Xinpeng Xing China
Robert M. Radway United States
Hector Gomez Colombia
Brian Crafton United States
William Hwang United States
Jonas Doevenspeck relative to Ioannis A. Papistas Belgium Ioannis A. Papistas's profile →
Citations per field
00.5×1.5×
Ioannis A. Papistas · 1×
Citations per year

Countries citing papers authored by Jonas Doevenspeck

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Doevenspeck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonas Doevenspeck, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonas Doevenspeck Line = papers co-authored together Jonas Doevenspeck links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 202253
2 201945
3 202128
4 202021
5 201814
6 202111
7
Multi-pillar SOT-MRAM for Accurate Analog in-Memory DNN Inference
20217
8 20225
9 20225
10 20185
11 20174
12 20214
13 20184
14 20182
15 20192
16 20191
17 20191
18
In-memory neural network computing with resistive memories
20211

About Jonas Doevenspeck

Jonas Doevenspeck is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Biomedical Engineering and Cognitive Neuroscience, having authored 18 papers that have together received 213 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (16 papers), Ferroelectric and Negative Capacitance Devices (14 papers), Semiconductor materials and devices (6 papers), Machine Learning and ELM (3 papers), Neural Networks and Applications (2 papers), Optical Network Technologies (1 paper), Fuel Cells and Related Materials (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Electrical and Electronic Engineering (194 citations), Hardware and Architecture (22 citations), Artificial Intelligence (49 citations), Computer Vision and Pattern Recognition (27 citations) and Bioengineering (6 citations). Jonas Doevenspeck has collaborated with scholars based in Belgium, United States and France. Frequent co-authors include Diederik Verkest, Peter Debacker, Stefan Cosemans, Ioannis A. Papistas, A. Mallik, Arindam Mallik, Francky Catthoor, Bram-Ernst Verhoef, Rudy Lauwereins and Peter Vrancx. Their work appears in journals such as IEEE Transactions on Electron Devices, Journal of Applied Physics, AIP Advances, ACM Transactions on Design Automation of Electronic Systems and Frontiers in Nanotechnology.

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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