David D. Yao

7.2k citations
164 papers · 4.6k indexed · h-index 40

Impact in

Papers in

David D. Yao

159 papers receiving 4.3k citations

Peers

David D. Yao
Comparison fields: 5 of 108
  • Management Information Systems 2.7k
  • Industrial and Manufacturing Engineering 1.6k
  • Management Science and Operations Research 1.0k
  • Statistics and Probability 357
  • Computer Networks and Communications 843
Replace Arthur F. Veinott with:
Arthur F. Veinott United States
Upendra Dave India
Michael C. Fu United States
Martin I. Reiman United States
John A. Buzacott Canada
Awi Federgruen United States
Gabriel R. Bitran United States
Paul Zipkin United States
Carl M. Harris United States
Herbert E. Scarf United States
David D. Yao relative to Arthur F. Veinott United States Arthur F. Veinott's profile →
Citations per field
00.5×1.5×1.8×
Arthur F. Veinott · 1×
Citations per year

Countries citing papers authored by David D. Yao

Since Specialization
Citations

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

Fields of papers citing papers by David D. Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David D. Yao. 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 David D. Yao. The network helps show where David D. Yao may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20234
4 202024
5 201817
6 201613
7 201651
8 20145
9 20044
10 200353
11 20035
12 200245
13 199921
14 198871
15 198720
16 1987101
17 198641
18 1986330
19 198549
20 198413

About David D. Yao

David D. Yao is a scholar working on Management Information Systems, Industrial and Manufacturing Engineering, Management Science and Operations Research, Statistics and Probability and Finance, having authored 164 papers that have together received 4.6k indexed citations. Recurring topics across this work include Advanced Queuing Theory Analysis (84 papers), Scheduling and Optimization Algorithms (32 papers), Supply Chain and Inventory Management (25 papers), Probability and Risk Models (23 papers), Advanced Wireless Network Optimization (14 papers), Petri Nets in System Modeling (14 papers), Network Traffic and Congestion Control (12 papers) and Simulation Techniques and Applications (12 papers). The work is most often cited by research in Management Information Systems (2.7k citations), Industrial and Manufacturing Engineering (1.6k citations), Management Science and Operations Research (1.0k citations), Statistics and Probability (357 citations) and Computer Networks and Communications (843 citations). David D. Yao has collaborated with scholars based in United States, Hong Kong and Canada. Frequent co-authors include J. George Shanthikumar, John A. Buzacott, Hong Chen, Paul Glasserman, Jing-Sheng Song, Markus Ettl, Grace Lin, Shaohui Zheng, Yingdong Lu and G. Feigin. Their work appears in journals such as Operations Research, Journal of Applied Probability, Production and Operations Management, ACM SIGMETRICS Performance Evaluation Review and Mathematics of Operations Research.

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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