Shubham Dodia
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Cellular and Molecular Neuroscience
- Pulmonary and Respiratory Medicine
- Co-authors
- Damodar Reddy EdlaAnnushree BablaniB. AnnappaP A MaheshVenkatanareshbabu KuppiliNidhi AroraRahul Kumar JainNeha Tiwari
- Topics
- EEG and Brain-Computer Interfaces (7 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Machine Learning and ELM (3 papers)
- Journals
- Expert Systems with ApplicationsIEEE Transactions on Information Forensics and SecurityJournal of Neuroscience Methods
- Partner nations
- India
In The Last Decade
Shubham Dodia
19 papers receiving 427 citations
Peers
Comparison fields: 5 of 93
- Cognitive Neuroscience 220
- Artificial Intelligence 135
- Radiology, Nuclear Medicine and Imaging 127
- Cellular and Molecular Neuroscience 62
- Pulmonary and Respiratory Medicine 53
Countries citing papers authored by Shubham Dodia
This map shows the geographic impact of Shubham Dodia'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 Shubham Dodia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shubham Dodia more than expected).
Fields of papers citing papers by Shubham Dodia
This network shows the impact of papers produced by Shubham Dodia. 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 Shubham Dodia. The network helps show where Shubham Dodia may publish in the future.
Co-authorship network of co-authors of Shubham Dodia
This figure shows the co-authorship network connecting the top 25 collaborators of Shubham Dodia. A scholar is included among the top collaborators of Shubham Dodia 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 Shubham Dodia. Shubham Dodia 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 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 44 | |
| 10 | 75 | |
| 11 | 21 | |
| 12 | 10 | |
| 13 | 35 | |
| 14 | 17 | |
| 15 | 18 | |
| 16 | 71 | |
| 17 | 36 | |
| 18 | 69 | |
| 19 | 18 | |
| 20 | 18 |
About Shubham Dodia
Shubham Dodia is a scholar working on Cognitive Neuroscience, Human-Computer Interaction and Artificial Intelligence, having authored 20 papers that have together received 445 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (7 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Machine Learning and ELM (3 papers). The work is most often cited by research in Cognitive Neuroscience (220 citations), Health Informatics (8 citations) and Radiology, Nuclear Medicine and Imaging (127 citations). Shubham Dodia has collaborated with scholars based in India. Frequent co-authors include Damodar Reddy Edla, Annushree Bablani, B. Annappa, P A Mahesh, Venkatanareshbabu Kuppili, Nidhi Arora, Rahul Kumar Jain, Neha Tiwari, Md Fahim Ansari and Dharavath Ramesh. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Information Forensics and Security and Journal of Neuroscience Methods.
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.