Larry Liu

747 citations
34 papers · 550 · h-index 10

Impact in

Papers in

Larry Liu

28 papers receiving 524 citations

Peers

Larry Liu
Comparison fields: 5 of 97
  • Family Practice 32
  • Computer Science Applications 109
  • Health Informatics 10
  • Epidemiology 176
  • Artificial Intelligence 103
Replace Yan Cheng with:
Yan Cheng United States
Kavishwar B. Wagholikar United States
Michael Chary United States
Ali Alshahrani Saudi Arabia
Gunther Schadow United States
R. R. O’Moore Ireland
Nathalie Texier France
Jonathan P. DeShazo United States
Zahra Niazkhani Iran
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Citations per field
00.5×6.3×
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Citations per year

Countries citing papers authored by Larry Liu

Since Specialization
Citations

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

Fields of papers citing papers by Larry Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004178
2 201791
3 201568
4
Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning.
201741
5 200640
6 202419
7 202117
8 200817
9 202012
10 20169
11 20228
12
A Case Study of Processing-in-Memory in off-the-Shelf Systems
20217
13 20227
14 20156
15 20045
16 20205
17 20204
18 20133
19 20222
20 20202

About Larry Liu

Larry Liu is a scholar working on Sociology and Political Science, General Health Professions, Political Science and International Relations, Finance and Artificial Intelligence, having authored 34 papers that have together received 550 indexed citations. Recurring topics across this work include Employment and Welfare Studies (5 papers), Labor Movements and Unions (3 papers), Housing, Finance, and Neoliberalism (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Digital Economy and Work Transformation (2 papers), China's Socioeconomic Reforms and Governance (2 papers), Integrated Circuits and Semiconductor Failure Analysis (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Family Practice (32 citations), Computer Science Applications (109 citations), Health Informatics (10 citations), Epidemiology (176 citations) and Artificial Intelligence (103 citations). Larry Liu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Gabrielle Ciesla, L. Clark Paramore, Vincent Ciuryla, Chris Piech, Lisa Wang, Bradi B. Granger, Walid F. Gellad, Leah L. Zullig, Christopher B. Granger and William H. Shrank. Their work appears in journals such as BMJ Open, PharmacoEconomics, Social Forces, Journal of Medicinal Chemistry and Ethnic and Racial Studies.

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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