Sandy H. Huang
- Clinical Psychology top 5%
- Artificial Intelligence top 10%
- Social Psychology top 10%
- General Health Professions top 10%
- Experimental and Cognitive Psychology top 10%
- Co-authors
- George A. BonannoIsaac R. Galatzer‐LevyPieter AbbeelAnca D. DraganDavid HeldMing Tai-SealePaea LePenduNigam H. Shah
- Topics
- Reinforcement Learning in Robotics (6 papers)Robot Manipulation and Learning (4 papers)AI-based Problem Solving and Planning (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaClinical Psychology ReviewAddiction
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Sandy H. Huang
16 papers receiving 864 citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Clinical Psychology 457
- Artificial Intelligence 172
- Social Psychology 129
- General Health Professions 96
- Experimental and Cognitive Psychology 86
Countries citing papers authored by Sandy H. Huang
This map shows the geographic impact of Sandy H. Huang'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 Sandy H. Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandy H. Huang more than expected).
Fields of papers citing papers by Sandy H. Huang
This network shows the impact of papers produced by Sandy H. Huang. 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 Sandy H. Huang. The network helps show where Sandy H. Huang may publish in the future.
Co-authorship network of co-authors of Sandy H. Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Sandy H. Huang. A scholar is included among the top collaborators of Sandy H. Huang 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 Sandy H. Huang. Sandy H. Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 16 | |
| 3 | 13 | |
| 4 | 32 | |
| 5 | 6 | |
| 6 | A Constrained Multi-Objective Reinforcement Learning Framework | 2 |
| 7 | 3 | |
| 8 | Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluationbreakdown → | 520 |
| 9 | 51 | |
| 10 | 66 | |
| 11 | 25 | |
| 12 | 29 | |
| 13 | 2 | |
| 14 | 77 | |
| 15 | 24 | |
| 16 | 23 |
About Sandy H. Huang
Sandy H. Huang is a scholar working on Applied Psychology, Artificial Intelligence and Control and Systems Engineering, having authored 16 papers that have together received 890 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Robot Manipulation and Learning (4 papers) and AI-based Problem Solving and Planning (3 papers). The work is most often cited by research in Clinical Psychology (457 citations), Applied Psychology (76 citations) and Health Informatics (9 citations). Sandy H. Huang has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include George A. Bonanno, Isaac R. Galatzer‐Levy, Pieter Abbeel, Anca D. Dragan, David Held, Ming Tai-Seale, Paea LePendu, Nigam H. Shah, Srinivasan Iyer and David Carrell. Their work appears in journals such as SHILAP Revista de lepidopterología, Clinical Psychology Review and Addiction.
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.