Abhinav Parate
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Human-Computer Interaction top 5%
- Artificial Intelligence
- Co-authors
- Deepak GanesanMeng‐Chieh ChiuEvangelos KalogerakisBenjamin M. MarlinDavid ChuMatthias BöhmerAnnamalai NatarajanRobert T. Malison
- Topics
- Context-Aware Activity Recognition Systems (3 papers)Green IT and Sustainability (2 papers)Privacy-Preserving Technologies in Data (2 papers)
- Journals
- Drug and Alcohol DependencePubMedScholarworks (University of Massachusetts Amherst)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Abhinav Parate
12 papers receiving 430 citations
Peers
Comparison fields: 5 of 75
- Electrical and Electronic Engineering 178
- Computer Vision and Pattern Recognition 132
- Computer Networks and Communications 120
- Human-Computer Interaction 86
- Artificial Intelligence 79
Countries citing papers authored by Abhinav Parate
This map shows the geographic impact of Abhinav Parate'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 Abhinav Parate with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhinav Parate more than expected).
Fields of papers citing papers by Abhinav Parate
This network shows the impact of papers produced by Abhinav Parate. 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 Abhinav Parate. The network helps show where Abhinav Parate may publish in the future.
Co-authorship network of co-authors of Abhinav Parate
This figure shows the co-authorship network connecting the top 25 collaborators of Abhinav Parate. A scholar is included among the top collaborators of Abhinav Parate 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 Abhinav Parate. Abhinav Parate 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 | 0 | |
| 3 | 8 | |
| 4 | Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams. | 5 |
| 5 | 2 | |
| 6 | 229 | |
| 7 | 2 | |
| 8 | 20 | |
| 9 | 122 | |
| 10 | 31 | |
| 11 | 8 | |
| 12 | A Framework for Utility-Driven Network Trace Anonymization | 2 |
| 13 | 1 | |
| 14 | 20 |
About Abhinav Parate
Abhinav Parate is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Applied Psychology, having authored 14 papers that have together received 450 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (3 papers), Green IT and Sustainability (2 papers) and Privacy-Preserving Technologies in Data (2 papers). The work is most often cited by research in Human-Computer Interaction (86 citations), Transportation (45 citations) and Computer Vision and Pattern Recognition (132 citations). Abhinav Parate has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Deepak Ganesan, Meng‐Chieh Chiu, Evangelos Kalogerakis, Benjamin M. Marlin, David Chu, Matthias Böhmer, Annamalai Natarajan, Robert T. Malison, Edward Gaiser and Gustavo A. Angarita. Their work appears in journals such as Drug and Alcohol Dependence, PubMed and Scholarworks (University of Massachusetts Amherst).
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.