Sachindra Joshi
- Artificial Intelligence top 2%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Signal Processing top 10%
- Co-authors
- Subhabrata MukherjeeRaghu KrishnapuramVineet KumarSong FengChulaka GunasekaraKrishna KummamuruBhushan MandhaniTanveer A. Faruquie
- Topics
- Topic Modeling (36 papers)Natural Language Processing Techniques (29 papers)Speech and dialogue systems (17 papers)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Sachindra Joshi
58 papers receiving 623 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 561
- Information Systems 196
- Computer Vision and Pattern Recognition 97
- Computer Networks and Communications 55
- Signal Processing 54
Countries citing papers authored by Sachindra Joshi
This map shows the geographic impact of Sachindra Joshi'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 Sachindra Joshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sachindra Joshi more than expected).
Fields of papers citing papers by Sachindra Joshi
This network shows the impact of papers produced by Sachindra Joshi. 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 Sachindra Joshi. The network helps show where Sachindra Joshi may publish in the future.
Co-authorship network of co-authors of Sachindra Joshi
This figure shows the co-authorship network connecting the top 25 collaborators of Sachindra Joshi. A scholar is included among the top collaborators of Sachindra Joshi 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 Sachindra Joshi. Sachindra Joshi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 8 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 57 | |
| 11 | Dialogue-act-driven Conversation Model : An Experimental Study | 5 |
| 12 | Non-sentential Question Resolution using Sequence to Sequence Learning | 12 |
| 13 | Sentiment Aggregation using ConceptNet Ontology | 25 |
| 14 | Finding Influential Authors in Brand-Age Communities | 7 |
| 15 | 40 | |
| 16 | Automated Concept Extraction to aid Legal eDiscovery Review | 2 |
| 17 | Learning Decision Lists with Known Rules for Text Mining | 3 |
| 18 | 11 | |
| 19 | 7 | |
| 20 | 7 |
About Sachindra Joshi
Sachindra Joshi is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 670 indexed citations. Recurring topics across this work include Topic Modeling (36 papers), Natural Language Processing Techniques (29 papers) and Speech and dialogue systems (17 papers). The work is most often cited by research in Artificial Intelligence (561 citations), Information Systems (196 citations) and Signal Processing (54 citations). Sachindra Joshi has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Subhabrata Mukherjee, Raghu Krishnapuram, Vineet Kumar, Song Feng, Chulaka Gunasekara, Krishna Kummamuru, Bhushan Mandhani, Tanveer A. Faruquie, Ashwin Srinivasan and Sumit Negi. Their work appears in journals such as Neurocomputing, Machine Learning and Proceedings of the VLDB Endowment.
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.