Ashima Khosla
Impact in
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
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- Emotion and Mood Recognition
Papers in
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- EEG and Brain-Computer Interfaces 4
- Functional Brain Connectivity Studies 2
- Neural dynamics and brain function 1
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- ECG Monitoring and Analysis 2
- Co-authors
- Trilok Chand (6 shared papers)Padmavati Khandnor (4 shared papers)Mahesh Prakash (2 shared papers)Neelesh Kumar (1 shared paper)Devendra Kumar Chouhan (2 shared papers)Trilok Chand Aseri (1 shared paper)
- Journals
- Journal of Applied Biomedicine (2 papers)International Journal of Imaging Systems and Technology (1 paper)Biomedical Signal Processing and Control (1 paper)Expert Systems (1 paper)Concurrency and Computation Practice and Experience (1 paper)
- Partner nations
- India
In The Last Decade
Ashima Khosla
8 papers receiving 263 citations
Peers
Comparison fields: 5 of 71
- Cognitive Neuroscience 195
- Experimental and Cognitive Psychology 54
- Signal Processing 35
- Human-Computer Interaction 17
- Cardiology and Cardiovascular Medicine 63
Countries citing papers authored by Ashima Khosla
This map shows the geographic impact of Ashima Khosla'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 Ashima Khosla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashima Khosla more than expected).
Fields of papers citing papers by Ashima Khosla
This network shows the impact of papers produced by Ashima Khosla. 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 Ashima Khosla. The network helps show where Ashima Khosla may publish in the future.
Co-authors
The 6 scholars most cited alongside Ashima Khosla, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 172 | |
| 2 | 2021 | 54 | |
| 3 | 2021 | 16 | |
| 4 | 2023 | 11 | |
| 5 | 2022 | 6 | |
| 6 | 2024 | 5 | |
| 7 | Comparative Analysis of Objective Functions in Routing Protocol for Low Power and Lossy Networks | 2018 | 2 |
| 8 | 2023 | 1 |
About Ashima Khosla
Ashima Khosla is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine, Signal Processing, Computer Networks and Communications and Molecular Biology, having authored 8 papers that have together received 267 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Blind Source Separation Techniques (2 papers), Functional Brain Connectivity Studies (2 papers), ECG Monitoring and Analysis (2 papers), Neural dynamics and brain function (1 paper), Machine Learning in Bioinformatics (1 paper), Energy Efficient Wireless Sensor Networks (1 paper) and Balance, Gait, and Falls Prevention (1 paper). The work is most often cited by research in Cognitive Neuroscience (195 citations), Experimental and Cognitive Psychology (54 citations), Signal Processing (35 citations), Human-Computer Interaction (17 citations) and Cardiology and Cardiovascular Medicine (63 citations). Ashima Khosla has collaborated with scholars based in India. Frequent co-authors include Trilok Chand, Padmavati Khandnor, Mahesh Prakash, Neelesh Kumar, Devendra Kumar Chouhan and Trilok Chand Aseri. Their work appears in journals such as Journal of Applied Biomedicine, International Journal of Imaging Systems and Technology, Biomedical Signal Processing and Control, Expert Systems and Concurrency and Computation Practice and Experience.
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.