Manohar Kaul
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Transportation top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Jatin ChauhanDeepak NathaniCharu SharmaChristian S. JensenBin YangChenjuan GuoShuo ShangArti Kashyap
- Topics
- Data Management and Algorithms (6 papers)Data Mining Algorithms and Applications (3 papers)Traffic Prediction and Management Techniques (3 papers)
In The Last Decade
Manohar Kaul
19 papers receiving 730 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 423
- Signal Processing 211
- Transportation 149
- Information Systems 127
- Computer Vision and Pattern Recognition 109
Countries citing papers authored by Manohar Kaul
This map shows the geographic impact of Manohar Kaul'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 Manohar Kaul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manohar Kaul more than expected).
Fields of papers citing papers by Manohar Kaul
This network shows the impact of papers produced by Manohar Kaul. 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 Manohar Kaul. The network helps show where Manohar Kaul may publish in the future.
Co-authorship network of co-authors of Manohar Kaul
This figure shows the co-authorship network connecting the top 25 collaborators of Manohar Kaul. A scholar is included among the top collaborators of Manohar Kaul 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 Manohar Kaul. Manohar Kaul is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | Higher-order Structure Prediction in Evolving Graph Simplicial Complexes | 1 |
| 5 | Self-Supervised Few-Shot Learning on Point Clouds | 1 |
| 6 | 11 | |
| 7 | Learning Attention-based Embeddings for Relation Prediction in
\nKnowledge Graphsbreakdown → | 351 |
| 8 | 1 | |
| 9 | 9 | |
| 10 | Improving Data Quality by Leveraging Statistical RelationalLearning | 4 |
| 11 | 15 | |
| 12 | 7 | |
| 13 | 46 | |
| 14 | 104 | |
| 15 | 2 | |
| 16 | 12 | |
| 17 | 58 | |
| 18 | 64 | |
| 19 | 49 | |
| 20 | 12 |
About Manohar Kaul
Manohar Kaul is a scholar working on Signal Processing, Geology and Transportation, having authored 20 papers that have together received 751 indexed citations. Recurring topics across this work include Data Management and Algorithms (6 papers), Data Mining Algorithms and Applications (3 papers) and Traffic Prediction and Management Techniques (3 papers). The work is most often cited by research in Transportation (149 citations), Signal Processing (211 citations) and Artificial Intelligence (423 citations). Manohar Kaul has collaborated with scholars based in India, Denmark and Germany. Frequent co-authors include Jatin Chauhan, Deepak Nathani, Charu Sharma, Christian S. Jensen, Bin Yang, Chenjuan Guo, Shuo Shang, Arti Kashyap, Yu Ma and Volker Markl. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment and SN Computer Science.
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.