Annushree Bablani
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 5%
- Accounting top 10%
- Social Psychology
- Signal Processing top 10%
- Co-authors
- Damodar Reddy EdlaChandra Sekhara Rao AnnavarapuShubham DodiaDiwakar TripathiVenkatanareshbabu KuppiliDharavath RameshRamalingaswamy CherukuNeha Tiwari
- Topics
- EEG and Brain-Computer Interfaces (14 papers)Deception detection and forensic psychology (10 papers)Adversarial Robustness in Machine Learning (7 papers)
- Journals
- ACM Computing SurveysIEEE Transactions on Information Forensics and SecurityIEEE Transactions on Instrumentation and Measurement
- Partner nations
- IndiaUnited Kingdom
In The Last Decade
Annushree Bablani
26 papers receiving 605 citations
Peers
Comparison fields: 5 of 101
- Cognitive Neuroscience 246
- Artificial Intelligence 238
- Accounting 74
- Social Psychology 73
- Signal Processing 68
Countries citing papers authored by Annushree Bablani
This map shows the geographic impact of Annushree Bablani'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 Annushree Bablani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annushree Bablani more than expected).
Fields of papers citing papers by Annushree Bablani
This network shows the impact of papers produced by Annushree Bablani. 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 Annushree Bablani. The network helps show where Annushree Bablani may publish in the future.
Co-authorship network of co-authors of Annushree Bablani
This figure shows the co-authorship network connecting the top 25 collaborators of Annushree Bablani. A scholar is included among the top collaborators of Annushree Bablani 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 Annushree Bablani. Annushree Bablani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 16 | |
| 5 | 25 | |
| 6 | 158 | |
| 7 | 11 | |
| 8 | 2 | |
| 9 | 45 | |
| 10 | 23 | |
| 11 | 35 | |
| 12 | 17 | |
| 13 | 18 | |
| 14 | 40 | |
| 15 | 71 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 21 | |
| 20 | 7 |
About Annushree Bablani
Annushree Bablani is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Social Psychology, having authored 27 papers that have together received 634 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (14 papers), Deception detection and forensic psychology (10 papers) and Adversarial Robustness in Machine Learning (7 papers). The work is most often cited by research in Cognitive Neuroscience (246 citations), Artificial Intelligence (238 citations) and Accounting (74 citations). Annushree Bablani has collaborated with scholars based in India and United Kingdom. Frequent co-authors include Damodar Reddy Edla, Chandra Sekhara Rao Annavarapu, Shubham Dodia, Diwakar Tripathi, Venkatanareshbabu Kuppili, Dharavath Ramesh, Ramalingaswamy Cheruku, Neha Tiwari, Alok Kumar Shukla and Saugat Bhattacharyya. Their work appears in journals such as ACM Computing Surveys, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Instrumentation and Measurement.
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.