Jie Lao

798 citations
20 papers · 680 indexed · 1 hit paper · h-index 15

Jie Lao

20 papers receiving 672 citations

Hit Papers

Ultralow‐Power Machine Vision with Self‐Powered Sensor Re...14020222026202320244080120

Peers

Jie Lao
Comparison fields: 5 of 39
  • Renewable Energy, Sustainability and the Environment 176
  • Electrical and Electronic Engineering 590
  • Polymers and Plastics 140
  • Cellular and Molecular Neuroscience 161
  • Electrochemistry 34
Replace Donggang Xie with:
Donggang Xie China
Atul C. Khot South Korea
Shuaipeng Ge China
Pengshan Xie Hong Kong
Haoming Yu United States
Nasir Ilyas China
Alpana Nayak India
Tongrui Sun China
Jun‐Hwe Cha South Korea
Nasir Ilyas China
Jie Lao relative to Donggang Xie China Donggang Xie's profile →
Citations per field
00.5×4.4×
Donggang Xie · 1×
Citations per year

Countries citing papers authored by Jie Lao

Since Specialization
Citations

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

Fields of papers citing papers by Jie Lao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202323
2 202334
3 202318
4 20224
5 202211
6 20223
7 202232
8
Ultralow‐Power Machine Vision with Self‐Powered Sensor Reservoirbreakdown →
2022140
9 20224
10 202183
11 202149
12 202120
13 20219
14 202027
15 202031
16 202024
17 202035
18 201937
19 201949
20 201947

About Jie Lao

Jie Lao is a scholar working on Cellular and Molecular Neuroscience, Renewable Energy, Sustainability and the Environment and Electrical and Electronic Engineering, having authored 20 papers that have together received 680 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (12 papers), Perovskite Materials and Applications (7 papers), Photoreceptor and optogenetics research (6 papers), Electrocatalysts for Energy Conversion (5 papers), Neural Networks and Reservoir Computing (4 papers), Neuroscience and Neural Engineering (4 papers), Conducting polymers and applications (3 papers) and Advanced battery technologies research (3 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (176 citations), Electrical and Electronic Engineering (590 citations) and Polymers and Plastics (140 citations). Jie Lao has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include Hui Peng, Chunhua Luo, Chunli Jiang, Hechun Lin, Chun‐Gang Duan, Bobo Tian, Ni Zhong, Ruijuan Qi, Rong Huang and Geoffrey I. N. Waterhouse. Their work appears in journals such as Chemical Engineering Journal, ACS Applied Materials & Interfaces and Journal of Catalysis.

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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