Jingyao Li

1.4k citations
60 papers · 1.1k indexed · 1 hit paper · h-index 16

Jingyao Li

49 papers receiving 1.0k citations

Hit Papers

Impact of climate policy uncertainty on traditional energ...3092022202620232024100200300

Peers

Jingyao Li
Comparison fields: 5 of 120
  • General Energy 39
  • Economics and Econometrics 488
  • Renewable Energy, Sustainability and the Environment 284
  • Finance 103
  • General Economics, Econometrics and Finance 40
Replace Xiong Xiong with:
Xiong Xiong China
Hong Cao China
Julien Chevallier France
Xueyong Liu China
Jihong Xiao China
Reza Hafezi Iran
Manuel Monge Spain
Song Song China
Jingyao Li relative to Xiong Xiong China Xiong Xiong's profile →
Citations per field
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Xiong Xiong · 1×
Citations per year

Countries citing papers authored by Jingyao Li

Since Specialization
Citations

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

Fields of papers citing papers by Jingyao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 20250
5 20245
6 20243
7 20232
8 202312
9 20233
10 202321
11 20231
12 20230
13
Impact of climate policy uncertainty on traditional energy and green markets: Evidence from time-varying granger testsbreakdown →
2022309
14 202211
15 202218
16 20211
17 20214
18 20203
19 201419
20 201378

About Jingyao Li

Jingyao Li is a scholar working on Computational Mathematics, Renewable Energy, Sustainability and the Environment and Artificial Intelligence, having authored 60 papers that have together received 1.1k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (10 papers), Advanced Photocatalysis Techniques (10 papers), Energy, Environment, Economic Growth (6 papers), Market Dynamics and Volatility (6 papers), Multimodal Machine Learning Applications (6 papers), Advanced Nanomaterials in Catalysis (4 papers), Gene expression and cancer classification (4 papers) and TiO2 Photocatalysis and Solar Cells (4 papers). The work is most often cited by research in General Energy (39 citations), Economics and Econometrics (488 citations) and Renewable Energy, Sustainability and the Environment (284 citations). Jingyao Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaohang Ren, Brian M. Lucey, Feng He, Xiong Wang, Zhanshan Li, Dongdong Lin, Hong‐Wen Deng, Shuai Lü, Jigang Zhang and Yu‐Ping Wang. Their work appears in journals such as Renewable and Sustainable Energy Reviews, Langmuir and Chemical Engineering Journal.

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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