Adit Krishnan
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
-
- Topic Modeling 11
- Advanced Graph Neural Networks 8
- Natural Language Processing Techniques 2
- Data Stream Mining Techniques 1
-
- Recommender Systems and Techniques 6
- Information Retrieval and Search Behavior 2
- Co-authors
- Hari Sundaram (9 shared papers)Aravind Sankar (6 shared papers)Xinyang Zhang (1 shared paper)Jiawei Han (1 shared paper)Ashish Arunkumar Sharma (1 shared paper)Mahashweta Das (2 shared papers)Hao Yang (1 shared paper)Sayan Ranu (2 shared papers)
- Journals
- World Wide Web (1 paper)Knowledge and Information Systems (1 paper)Lecture notes in computer science (3 papers)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Adit Krishnan
14 papers receiving 275 citations
Peers
Comparison fields: 5 of 31
- Information Systems 171
- Statistical and Nonlinear Physics 72
- Artificial Intelligence 195
- Management Science and Operations Research 47
- Computer Vision and Pattern Recognition 37
Countries citing papers authored by Adit Krishnan
This map shows the geographic impact of Adit Krishnan'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 Adit Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adit Krishnan more than expected).
Fields of papers citing papers by Adit Krishnan
This network shows the impact of papers produced by Adit Krishnan. 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 Adit Krishnan. The network helps show where Adit Krishnan may publish in the future.
Co-authors
The 21 scholars most cited alongside Adit Krishnan, 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 | 2020 | 68 | |
| 2 | 2018 | 59 | |
| 3 | 2020 | 53 | |
| 4 | 2019 | 28 | |
| 5 | 2017 | 20 | |
| 6 | 2021 | 15 | |
| 7 | 2016 | 8 | |
| 8 | 2018 | 8 | |
| 9 | 2019 | 4 | |
| 10 | 2021 | 3 | |
| 11 | 2022 | 3 | |
| 12 | 2015 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 0 |
About Adit Krishnan
Adit Krishnan is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 275 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Advanced Graph Neural Networks (8 papers), Recommender Systems and Techniques (6 papers), Information Retrieval and Search Behavior (2 papers), Natural Language Processing Techniques (2 papers), Complex Network Analysis Techniques (2 papers), Rough Sets and Fuzzy Logic (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Information Systems (171 citations), Statistical and Nonlinear Physics (72 citations), Artificial Intelligence (195 citations), Management Science and Operations Research (47 citations) and Computer Vision and Pattern Recognition (37 citations). Adit Krishnan has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Hari Sundaram, Aravind Sankar, Xinyang Zhang, Jiawei Han, Ashish Arunkumar Sharma, Mahashweta Das, Hao Yang, Sayan Ranu, Sameep Mehta and Pradeep Kumar Deepak. Their work appears in journals such as World Wide Web, Knowledge and Information Systems, Lecture notes in computer science and arXiv (Cornell University).
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.