Hong Xie

1.7k citations
129 papers · 1.2k indexed · 1 hit paper · h-index 19

Hong Xie

107 papers receiving 1.1k citations

Hit Papers

Multi-Objective Workflow Scheduling With Deep-Q-Network-B...221201920262021202350100150200

Peers

Hong Xie
Comparison fields: 5 of 129
  • Computer Science Applications 98
  • Information Systems 240
  • Management Science and Operations Research 127
  • Computer Networks and Communications 224
  • Artificial Intelligence 278
Replace Lichen Zhang with:
Lichen Zhang China
Yafei Li China
Wei Song China
Qing Zhang China
Xiang Lian China
Zehui Shao China
Qingyu Yang China
Chunhong Zhang China
Yongrui Qin United Kingdom
Hong Xie relative to Lichen Zhang China Lichen Zhang's profile →
Citations per field
00.5×1.5×2.3×
Lichen Zhang · 1×
Citations per year

Countries citing papers authored by Hong Xie

Since Specialization
Citations

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

Fields of papers citing papers by Hong Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20253
4 20250
5 20251
6 20240
7 20230
8 20233
9 20232
10 20231
11 20233
12 20235
13 20233
14 20220
15 20221
16 202030
17
Multi-Objective Workflow Scheduling With Deep-Q-Network-Based Multi-Agent Reinforcement Learningbreakdown →
2019221
18 20170
19
Cybersecurity Practices for E-Government: An Assessment in Bhutan
20158
20 19943

About Hong Xie

Hong Xie is a scholar working on Management Science and Operations Research, Computer Science Applications and Artificial Intelligence, having authored 129 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (16 papers), Auction Theory and Applications (14 papers), Complex Network Analysis Techniques (14 papers), Recommender Systems and Techniques (10 papers), Privacy-Preserving Technologies in Data (10 papers), Mobile Crowdsensing and Crowdsourcing (10 papers), Caching and Content Delivery (9 papers) and Data Stream Mining Techniques (8 papers). The work is most often cited by research in Computer Science Applications (98 citations), Information Systems (240 citations) and Management Science and Operations Research (127 citations). Hong Xie has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include John C. S. Lui, Yunni Xia, Yawen Li, Yuandou Wang, Peng Chen, Wanbo Zheng, Yung-Cheng Lee, Guanhui Li, Gaoyuan Hou and Dejian Zhang. Their work appears in journals such as Food Chemistry, ACS Applied Materials & Interfaces and Chemosphere.

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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