Adish Singla

2.6k citations
64 papers · 972 · h-index 13

Impact in

Papers in

Adish Singla

57 papers receiving 938 citations

Peers

Adish Singla
Comparison fields: 5 of 82
  • Computer Science Applications 311
  • Transportation 157
  • Management Science and Operations Research 226
  • Health Informatics 19
  • Artificial Intelligence 400
Replace Caleb Chen Cao with:
Caleb Chen Cao Hong Kong
Zhixu Li China
Jieying She Hong Kong
Mihajlo Grbovic United States
Alper Bilge Türkiye
Yudian Zheng China
Shengling Wang China
Lirong Xia United States
Adish Singla relative to Caleb Chen Cao Hong Kong Caleb Chen Cao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Adish Singla

Since Specialization
Citations

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

Fields of papers citing papers by Adish Singla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013195
2 2018150
3 2015147
4 202345
5 201440
6 201437
7 201437
8 201036
9 201430
10 201723
11 202420
12 202314
13
Interactive Teaching Algorithms for Inverse Reinforcement Learning
201913
14 201412
15 201211
16 201811
17
Explicable Reward Design for Reinforcement Learning Agents
202110
18 20108
19 20168
20
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
20197

About Adish Singla

Adish Singla is a scholar working on Artificial Intelligence, Computer Science Applications, Management Science and Operations Research, Information Systems and Sociology and Political Science, having authored 64 papers that have together received 972 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (17 papers), Reinforcement Learning in Robotics (11 papers), Auction Theory and Applications (8 papers), Machine Learning and Algorithms (8 papers), Teaching and Learning Programming (7 papers), Advanced Bandit Algorithms Research (7 papers), Information Retrieval and Search Behavior (6 papers) and Complex Network Analysis Techniques (5 papers). The work is most often cited by research in Computer Science Applications (311 citations), Transportation (157 citations), Management Science and Operations Research (226 citations), Health Informatics (19 citations) and Artificial Intelligence (400 citations). Adish Singla has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Andreas Krause, Sebastian Tschiatschek, Manuel Gomez-Rodriguez, Gábor Bartók, Ryen W. White, Afshin Nikzad, Gagan Goel, Jeff Huang, Andreas Krause and Gustavo Soares. Their work appears in journals such as Journal of Imaging Science and Technology, Management Science, ACM Transactions on the Web, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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