Larry Chan
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Applied Psychology top 10%
- Digital Mental Health Interventions
Papers in
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- Topic Modeling 3
- Explainable Artificial Intelligence (XAI) 3
- Reinforcement Learning in Robotics 2
- Artificial Intelligence in Games 1
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- Mental Health Research Topics 2
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes 1
- Co-authors
- Upol Ehsan (4 shared papers)Mark Riedl (4 shared papers)Brent Harrison (3 shared papers)Pradyumna Tambwekar (2 shared papers)Kaya de Barbaro (2 shared papers)Gregory D. Abowd (2 shared papers)Koustuv Saha (1 shared paper)Munmun De Choudhury (1 shared paper)
- Journals
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2 papers)Zenodo (CERN European Organization for Nuclear Research) (1 paper)UKnowledge (University of Kentucky) (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Larry Chan
8 papers receiving 338 citations
Peers
Comparison fields: 5 of 64
- Health Informatics 43
- Applied Psychology 50
- Safety Research 71
- Artificial Intelligence 209
- Information Systems and Management 28
Countries citing papers authored by Larry Chan
This map shows the geographic impact of Larry Chan'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 Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Larry Chan more than expected).
Fields of papers citing papers by Larry Chan
This network shows the impact of papers produced by Larry Chan. 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 Chan. The network helps show where Larry Chan may publish in the future.
Co-authors
The 18 scholars most cited alongside Larry Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 148 | |
| 2 | 2018 | 68 | |
| 3 | 2017 | 59 | |
| 4 | 2024 | 42 | |
| 5 | 2018 | 31 | |
| 6 | Learning to Generate Natural Language Rationales for Game Playing Agents | 2018 | 2 |
| 7 | 2016 | 1 | |
| 8 | 2016 | 1 |
About Larry Chan
Larry Chan is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology, Applied Psychology, Communication and History and Philosophy of Science, having authored 8 papers that have together received 352 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Mental Health Research Topics (2 papers), Reinforcement Learning in Robotics (2 papers), Artificial Intelligence in Games (1 paper), Behavioral Health and Interventions (1 paper), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (1 paper) and Wikis in Education and Collaboration (1 paper). The work is most often cited by research in Health Informatics (43 citations), Applied Psychology (50 citations), Safety Research (71 citations), Artificial Intelligence (209 citations) and Information Systems and Management (28 citations). Larry Chan has collaborated with scholars based in United States and China. Frequent co-authors include Upol Ehsan, Mark Riedl, Brent Harrison, Pradyumna Tambwekar, Kaya de Barbaro, Gregory D. Abowd, Koustuv Saha, Munmun De Choudhury, Samir Passi and Q. Vera Liao. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Zenodo (CERN European Organization for Nuclear Research) and UKnowledge (University of Kentucky).
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.