Chieh-Jan Mike Liang

2.0k citations
42 papers · 1.5k indexed · h-index 17

Chieh-Jan Mike Liang

41 papers receiving 1.4k citations

Peers

Chieh-Jan Mike Liang
Comparison fields: 5 of 81
  • Computer Networks and Communications 1.1k
  • Software 88
  • Hardware and Architecture 96
  • Signal Processing 127
  • Electrical and Electronic Engineering 676
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Citations per year

Countries citing papers authored by Chieh-Jan Mike Liang

Since Specialization
Citations

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

Fields of papers citing papers by Chieh-Jan Mike Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chieh-Jan Mike Liang. 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 Chieh-Jan Mike Liang. The network helps show where Chieh-Jan Mike Liang may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20243
2
AutoSys: The Design and Operation of Learning-Augmented Systems.
20206
3
Accelerating Rule-matching Systems with Learned Rankers.
20192
4 20191
5 20194
6
Metis: robustly optimizing tail latencies of cloud systems
20183
7
Metis: Robustly Tuning Tail Latencies of Cloud Systems
201814
8 20175
9 201716
10
Memory-centric data storage for mobile systems
20159
11 20151
12 20145
13
Location-log: Bringing Online Shopping Benefits to the Physical World with Magnetic-based Proximity Detection
20123
14 201213
15 20120
16 201240
17 201224
18 20108
19
Life Under Your Feet: A Wireless Soil Ecology Sensor Network
200851
20 2008157

About Chieh-Jan Mike Liang

Chieh-Jan Mike Liang is a scholar working on Computer Networks and Communications, Software and Computer Science Applications, having authored 42 papers that have together received 1.5k indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (15 papers), Mobile Ad Hoc Networks (7 papers), Green IT and Sustainability (6 papers), Opportunistic and Delay-Tolerant Networks (6 papers), Context-Aware Activity Recognition Systems (6 papers), Energy Harvesting in Wireless Networks (5 papers), Wireless Networks and Protocols (5 papers) and Indoor and Outdoor Localization Technologies (4 papers). The work is most often cited by research in Computer Networks and Communications (1.1k citations), Software (88 citations) and Hardware and Architecture (96 citations). Chieh-Jan Mike Liang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Andreas Terzis, Jie Liu, Nissanka B. Priyantha, Răzvan Musăloiu-E., Prabal Dutta, Stephen Dawson-Haggerty, Chen Yin, Feng Zhao, Sirajum Munir and John A. Stankovic. Their work appears in journals such as IEEE Communications Letters, IEEE Transactions on Mobile Computing and Proceedings of the VLDB Endowment.

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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