Miao Liu

2.2k citations
77 papers · 612 indexed · h-index 15
Topics
Reinforcement Learning in Robotics (11 papers)Speech and Audio Processing (6 papers)Embedded Systems Design Techniques (6 papers)
Partner nations
ChinaUnited StatesMacao

In The Last Decade

Miao Liu

68 papers receiving 590 citations

Peers

Miao Liu
Comparison fields: 5 of 84
  • Computer Vision and Pattern Recognition 217
  • Artificial Intelligence 156
  • Computer Networks and Communications 104
  • Hardware and Architecture 74
  • Electrical and Electronic Engineering 72
Replace Gerhard K. Kraetzschmar with:
Gerhard K. Kraetzschmar Germany
Damian M. Lyons United States
K. Rangarajan India
Rocco Fazzolari Italy
L.M. Patnaik India
Athanasios Kakarountas Greece
Hsu‐Chun Yen Taiwan
Biao Hu China
Xiang Long China
Diego Rodríguez-Losada Spain
Miao Liu relative to Gerhard K. Kraetzschmar Germany Gerhard K. Kraetzschmar's profile →
Citations per field
00.5×10×13×
Gerhard K. Kraetzschmar · 1×
Citations per year

Countries citing papers authored by Miao Liu

Since Specialization
Citations

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

Fields of papers citing papers by Miao Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miao Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Miao Liu. A scholar is included among the top collaborators of Miao Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miao Liu. Miao Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
3 0
4 0
5 2
6 3
7 4
8
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
1
9 2
10 50
11 7
12
Eigenoption Discovery through the Deep Successor Representation
2
13
Deep Reinforcement Learning for Accelerating the Convergence Rate
0
14
Online expectation maximization for reinforcement learning in POMDPs
2
15
Delay characteristics analysis and design of Ethernet CAN bus converter
1
16
The Infinite Regionalized Policy Representation
10
17
Research of Embedded Debug Based on JTAG
1
18 38
19
Design and Reality of Grid Storage Architecture Based on LVM and Soft-RAID
1
20 15

About Miao Liu

Miao Liu is a scholar working on Artificial Intelligence, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 77 papers that have together received 612 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (11 papers), Speech and Audio Processing (6 papers) and Embedded Systems Design Techniques (6 papers). The work is most often cited by research in Hardware and Architecture (74 citations), Computer Vision and Pattern Recognition (217 citations) and Human-Computer Interaction (27 citations). Miao Liu has collaborated with scholars based in China, United States and Macao. Frequent co-authors include James M. Rehg, Jonathan P. How, Yin Li, Hongxing Wei, Meng Wang, Zili Shao, Christopher Amato, Shourui Yang, Jigui Zhu and Jiahui Song. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Automatica.

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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