Jesse Engel

27 papers receiving 834 citations

Peers

Jesse Engel
Comparison fields: 5 of 69
  • Signal Processing 194
  • Computer Vision and Pattern Recognition 193
  • Materials Chemistry 414
  • Electrical and Electronic Engineering 468
  • Electronic, Optical and Magnetic Materials 101
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Countries citing papers authored by Jesse Engel

Since Specialization
Citations

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

Fields of papers citing papers by Jesse Engel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jesse Engel, 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 Jesse Engel Line = papers co-authored together Jesse Engel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011197
2 2013123
3 2014119
4 201851
5 201239
6
Persistent RNNs: stashing recurrent weights on-chip
201636
7 201332
8 201332
9 201630
10 202028
11
GANSynth: Adversarial Neural Audio Synthesis
201926
12
Hierarchical Variational Autoencoders for Music
201722
13
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
201818
14 201318
15 201915
16 202213
17
MidiMe: Personalizing a MusicVAE model with user data
201912
18 201812
19 201910
20 20206

About Jesse Engel

Jesse Engel is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Materials Chemistry, Electrical and Electronic Engineering and Artificial Intelligence, having authored 28 papers that have together received 865 indexed citations. Recurring topics across this work include Music and Audio Processing (16 papers), Music Technology and Sound Studies (10 papers), Speech and Audio Processing (8 papers), Quantum Dots Synthesis And Properties (6 papers), Speech Recognition and Synthesis (4 papers), Chalcogenide Semiconductor Thin Films (4 papers), Advanced Memory and Neural Computing (4 papers) and Copper-based nanomaterials and applications (3 papers). The work is most often cited by research in Signal Processing (194 citations), Computer Vision and Pattern Recognition (193 citations), Materials Chemistry (414 citations), Electrical and Electronic Engineering (468 citations) and Electronic, Optical and Magnetic Materials (101 citations). Jesse Engel has collaborated with scholars based in United States, Taiwan and Germany. Frequent co-authors include A. Paul Alivisatos, Adam P. Roberts, Vivian E. Ferry, Trevor Ewers, Sarah L. Swisher, Wanli Ma, Harry A. Atwater, Sarah White, Prashant K. Jain and Karthish Manthiram. Their work appears in journals such as Scientific Reports, ACS Nano, Journal of the American Chemical Society, Chemistry of Materials and Angewandte Chemie International Edition.

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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