Ming Fu

405 citations
24 papers · 290 · h-index 8

Impact in

Papers in

Ming Fu

23 papers receiving 287 citations

Peers

Ming Fu
Comparison fields: 5 of 18
  • Hardware and Architecture 138
  • Computer Networks and Communications 199
  • Artificial Intelligence 216
  • Computational Theory and Mathematics 96
  • Software 19
Replace KC Sivaramakrishnan with:
KC Sivaramakrishnan United States
Filip Sieczkowski Denmark
Fridtjof B. Siebert Germany
Jérémie Koenig United States
Jean Pichon-Pharabod United Kingdom
Ben Lippmeier Australia
Aleš Bizjak Denmark
Jan Schwinghammer Germany
Alceste Scalas United Kingdom
Dominic P. Mulligan United Kingdom
Ming Fu relative to KC Sivaramakrishnan United States KC Sivaramakrishnan's profile →
Citations per field
00.5×1.5×2×
KC Sivaramakrishnan · 1×
Citations per year

Countries citing papers authored by Ming Fu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201655
2 201241
3 201240
4 201039
5 202131
6 201425
7 201916
8 201211
9 20174
10 20213
11 20213
12 20193
13 20153
14 20233
15 20192
16 20102
17 20092
18 20072
19 20251
20 20121

About Ming Fu

Ming Fu is a scholar working on Hardware and Architecture, Computer Networks and Communications, Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 290 indexed citations. Recurring topics across this work include Distributed systems and fault tolerance (15 papers), Parallel Computing and Optimization Techniques (13 papers), Logic, programming, and type systems (9 papers), Security and Verification in Computing (7 papers), Real-Time Systems Scheduling (4 papers), Formal Methods in Verification (4 papers), Embedded Systems Design Techniques (2 papers) and Green IT and Sustainability (1 paper). The work is most often cited by research in Hardware and Architecture (138 citations), Computer Networks and Communications (199 citations), Artificial Intelligence (216 citations), Computational Theory and Mathematics (96 citations) and Software (19 citations). Ming Fu has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Xinyu Feng, Hongjin Liang, Zhong Shao, Zhaohui Li, Hui Zhang, Xiaoran Zhang, Fengwei Xu, Yu Zhang, Yong Li and Haibo Chen. Their work appears in journals such as Frontiers of Computer Science, ACM Transactions on Programming Languages and Systems, ACM SIGPLAN Notices, Science of Computer Programming and Lecture notes in computer science.

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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