Ming Yang

235 papers receiving 4.2k citations

Hit Papers

Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control 2020 · 235 citations
2350+2+4Years since publication50100150200

Peers

Ming Yang
Comparison fields: 5 of 165
  • Statistics, Probability and Uncertainty 1.9k
  • Radiological and Ultrasound Technology 897
  • Chemical Health and Safety 67
  • Safety, Risk, Reliability and Quality 652
  • Ocean Engineering 722
Replace Salim Ahmed with:
Salim Ahmed Canada
Laibin Zhang China
Guoming Chen China
Faisal Khan Ireland
Vikram Garaniya Australia
Joaquim Casal Spain
Baoping Cai China
Michael Havbro Faber Denmark
Xinping Yan China
Ming Yang relative to Salim Ahmed Canada Salim Ahmed's profile →
Citations per field
00.5×1.7×
Salim Ahmed · 1×
Citations per year

Countries citing papers authored by Ming Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ming Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 250 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control
Hit paper breakdown →
2020235
2 2017160
3 2017144
4 202091
5 202290
6 201277
7 201772
8 201072
9 202069
10 201965
11 201965
12 201859
13 202358
14 201858
15 201557
16 201654
17 202153
18 201352
19 201952
20 201551

About Ming Yang

Ming Yang is a scholar working on Statistics, Probability and Uncertainty, Radiological and Ultrasound Technology, Safety, Risk, Reliability and Quality, Control and Systems Engineering and Aerospace Engineering, having authored 250 papers that have together received 4.3k indexed citations. Recurring topics across this work include Risk and Safety Analysis (129 papers), Occupational Health and Safety Research (51 papers), Reliability and Maintenance Optimization (28 papers), Fault Detection and Control Systems (26 papers), Infrastructure Resilience and Vulnerability Analysis (23 papers), Structural Integrity and Reliability Analysis (21 papers), Nuclear Engineering Thermal-Hydraulics (15 papers) and Software Reliability and Analysis Research (14 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.9k citations), Radiological and Ultrasound Technology (897 citations), Chemical Health and Safety (67 citations), Safety, Risk, Reliability and Quality (652 citations) and Ocean Engineering (722 citations). Ming Yang has collaborated with scholars based in China, Netherlands and Canada. Frequent co-authors include Faisal Khan, Brian Veitch, Genserik Reniers, Sunday Adedigba, Mawuli Afenyo, Faisal Khan, Hidekazu Yoshikawa, Shuaiqi Yuan, Xinhong Li and Nima Khakzad. Their work appears in journals such as Process Safety and Environmental Protection, Reliability Engineering & System Safety, Journal of Loss Prevention in the Process Industries, Annals of Nuclear Energy and Ocean Engineering.

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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