Ming Jin

3.5k citations
83 papers · 2.5k indexed · h-index 27

Ming Jin

79 papers receiving 2.4k citations

Peers

Ming Jin
Comparison fields: 5 of 116
  • Building and Construction 624
  • Energy Engineering and Power Technology 108
  • Control and Systems Engineering 770
  • Environmental Engineering 302
  • Electrical and Electronic Engineering 1.2k
Replace Qing‐Shan Jia with:
Qing‐Shan Jia China
Alfonso Capozzoli Italy
Phuong H. Nguyen Netherlands
Di Wu China
Mary Ann Piette United States
Madeleine Gibescu Netherlands
Jin Wen United States
Prabir Barooah United States
M. Fesanghary United States
Doug Creighton Australia
Ming Jin relative to Qing‐Shan Jia China Qing‐Shan Jia's profile →
Citations per field
00.5×1.5×
Qing‐Shan Jia · 1×
Citations per year

Countries citing papers authored by Ming Jin

Since Specialization
Citations

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

Fields of papers citing papers by Ming Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20241
4 20244
5 20231
6 20236
7 202212
8 20223
9 202138
10 20202
11 202070
12 201930
13 201863
14 20173
15 20175
16 201612
17
Inverse Reinforcement Learning via Deep Gaussian Process
20152
18 20151
19
A BIM-enabled MEP coordination process for use in China
201424
20 200412

About Ming Jin

Ming Jin is a scholar working on Energy Engineering and Power Technology, Building and Construction, Transportation, Control and Systems Engineering and Health Informatics, having authored 83 papers that have together received 2.5k indexed citations. Recurring topics across this work include Smart Grid Energy Management (17 papers), Building Energy and Comfort Optimization (11 papers), Indoor and Outdoor Localization Technologies (9 papers), Microgrid Control and Optimization (8 papers), Smart Grid Security and Resilience (8 papers), Power System Optimization and Stability (6 papers), Adversarial Robustness in Machine Learning (5 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Building and Construction (624 citations), Energy Engineering and Power Technology (108 citations), Control and Systems Engineering (770 citations), Environmental Engineering (302 citations) and Electrical and Electronic Engineering (1.2k citations). Ming Jin has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Costas J. Spanos, Wei Feng, Chris Marnay, Stefano Schiavon, Javad Lavaei, Ruoxi Jia, Shichao Liu, Han Zou, H. Das and Alexandre M. Bayen. Their work appears in journals such as Applied Energy, Building and Environment, Sensors, IEEE Control Systems Letters and IEEE Transactions on Smart Grid.

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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