Tianyu Wang

3.7k citations
73 papers · 2.3k indexed · 3 hit papers · h-index 21
Topics
Advanced Memory and Neural Computing (16 papers)Neural Networks and Reservoir Computing (15 papers)Advanced Fluorescence Microscopy Techniques (14 papers)
Partner nations
United StatesChinaJapan

In The Last Decade

Tianyu Wang

62 papers receiving 2.2k citations

Hit Papers

Deep physical neural networks trained with backpropagation2022202620232024202220232022100200300400

Peers

Tianyu Wang
Comparison fields: 5 of 133
  • Electrical and Electronic Engineering 1.1k
  • Biomedical Engineering 583
  • Artificial Intelligence 582
  • Biophysics 537
  • Cellular and Molecular Neuroscience 442
Replace Hao Xie with:
Hao Xie China
Jiamin Wu China
Ke Wang China
Wibool Piyawattanametha United States
Jesper Glückstad Denmark
Dimitre G. Ouzounov United States
Xing Lin China
Jun Ohta Japan
Changliang Guo China
Michael J. Levene United States
Tianyu Wang relative to Hao Xie China Hao Xie's profile →
Citations per field
00.5×
Hao Xie · 1×
Citations per year

Countries citing papers authored by Tianyu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Tianyu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianyu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Tianyu Wang. A scholar is included among the top collaborators of Tianyu Wang 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 Tianyu Wang. Tianyu Wang 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
#WorkIndexed citations
1 0
2 1
3 0
4 10
5 0
6 6
7 2
8 1
9 4
10 1
11
Image sensing with multilayer nonlinear optical neural networksbreakdown →
159
12
Deep physical neural networks trained with backpropagationbreakdown →
421
13 22
14 37
15 15
16 16
17 27
18 21
19 332
20 1

About Tianyu Wang

Tianyu Wang is a scholar working on Biophysics, Acoustics and Ultrasonics and Cellular and Molecular Neuroscience, having authored 73 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (16 papers), Neural Networks and Reservoir Computing (15 papers) and Advanced Fluorescence Microscopy Techniques (14 papers). The work is most often cited by research in Biophysics (537 citations), Acoustics and Ultrasonics (65 citations) and Cellular and Molecular Neuroscience (442 citations). Tianyu Wang has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Chris Xu, Logan G. Wright, Peter L. McMahon, Tatsuhiro Onodera, Martin M. Stein, Dimitre G. Ouzounov, Darren T. Schachter, Zoey Hu, Nicholas G. Horton and Shi-Yuan Ma. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences 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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