Mei Si

1.2k citations
44 papers · 582 · h-index 12

Impact in

Papers in

    • Artificial Intelligence in Games 11
    • Multi-Agent Systems and Negotiation 8
    • Speech and dialogue systems 4
    • Topic Modeling 4
    • Reinforcement Learning in Robotics 4
    • Social Robot Interaction and HRI 8

Mei Si

39 papers receiving 541 citations

Peers

Mei Si
Comparison fields: 5 of 87
  • Artificial Intelligence 297
  • Human-Computer Interaction 31
  • Experimental and Cognitive Psychology 65
  • Clinical Psychology 87
  • Developmental and Educational Psychology 45
Replace Nadia Mana with:
Nadia Mana Italy
Michael Freed United States
Shogo Okada Japan
Sander Bakkes Netherlands
Arnav Jhala United States
Ravinder Ahuja India
Curry Guinn United States
Hasan Mahmud Bangladesh
Samer Muthana Sarsam Malaysia
Paolo Petta Austria
Mei Si relative to Nadia Mana Italy Nadia Mana's profile →
Citations per field
00.5×7.4×
Nadia Mana · 1×
Citations per year

Countries citing papers authored by Mei Si

Since Specialization
Citations

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

Fields of papers citing papers by Mei Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202089
2 201278
3 200378
4 200547
5 200536
6 202232
7 201932
8 200929
9 201221
10 201216
11 201011
12 201511
13 201410
14 20169
15 20248
16 20087
17 20147
18 20127
19 20155
20 20164

About Mei Si

Mei Si is a scholar working on Artificial Intelligence, Social Psychology, Control and Systems Engineering, Sociology and Political Science and Experimental and Cognitive Psychology, having authored 44 papers that have together received 582 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (11 papers), Multi-Agent Systems and Negotiation (8 papers), Social Robot Interaction and HRI (8 papers), Digital Games and Media (7 papers), Human Motion and Animation (6 papers), Speech and dialogue systems (4 papers), Topic Modeling (4 papers) and Reinforcement Learning in Robotics (4 papers). The work is most often cited by research in Artificial Intelligence (297 citations), Human-Computer Interaction (31 citations), Experimental and Cognitive Psychology (65 citations), Clinical Psychology (87 citations) and Developmental and Educational Psychology (45 citations). Mei Si has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Owen Lockwood, David V. Pynadath, Stacy Marsella, Xinghua Liu, Wenjun Chen, Paul Scerri, Paul S. Rosenbloom, Nathan Schurr, Milind Tambe and Yuzheng Wang. Their work appears in journals such as The Journal of the Acoustical Society of America, International Journal of Artificial Intelligence in Education, Mindfulness, Autonomous Agents and Multi-Agent Systems and Stress and Health.

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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