Rita Chattopadhyay
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Algorithms 3
- Machine Learning and Data Classification 3
- Anomaly Detection Techniques and Applications 3
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- Hand Gesture Recognition Systems 3
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- Muscle activation and electromyography studies 7
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- Emotion and Mood Recognition 5
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- EEG and Brain-Computer Interfaces 4
- Co-authors
- Sethuraman PanchanathanJieping YeIan DavidsonQian SunWei FanZheng WangGaurav N. PradhanNarayanan C. Krishnan
- Journals
- ACM Transactions on Knowledge Discovery from Data (2 papers)IEEE Transactions on Biomedical Engineering (1 paper)IEEE Internet of Things Journal (1 paper)
- Partner nations
- United StatesGermanyRussia
In The Last Decade
Rita Chattopadhyay
15 papers receiving 448 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 354
- Computer Vision and Pattern Recognition 174
- Human-Computer Interaction 13
- Media Technology 16
- Cancer Research 26
Countries citing papers authored by Rita Chattopadhyay
This map shows the geographic impact of Rita Chattopadhyay'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 Rita Chattopadhyay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rita Chattopadhyay more than expected).
Fields of papers citing papers by Rita Chattopadhyay
This network shows the impact of papers produced by Rita Chattopadhyay. 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 Rita Chattopadhyay. The network helps show where Rita Chattopadhyay may publish in the future.
Co-authorship network
The 19 scholars most cited alongside Rita Chattopadhyay, 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 | 2024 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | Joint Transfer and Batch-mode Active Learning | 2013 | 49 |
| 5 | 2013 | 52 | |
| 6 | 2012 | 6 | |
| 7 | 2012 | 32 | |
| 8 | 2012 | 110 | |
| 9 | Transfer Learning Framework for Early Detection of Fatigue Using Noninvasive Surface Electromyogram Signals (SEMG) | 2011 | 1 |
| 10 | A Two-Stage Weighting Framework for Multi-Source Domain Adaptation | 2011 | 122 |
| 11 | 2011 | 1 | |
| 12 | Topology Preserving Domain Adaptation for Addressing Subject Based Variability in SEMG Signal | 2011 | 15 |
| 13 | 2011 | 55 | |
| 14 | 2011 | 1 | |
| 15 | 2011 | 6 | |
| 16 | 2010 | 9 | |
| 17 | 2010 | 6 | |
| 18 | 2006 | 0 | |
| 19 | 2006 | 2 | |
| 20 | 2006 | 2 |
About Rita Chattopadhyay
Rita Chattopadhyay is a scholar working on Human-Computer Interaction, Experimental and Cognitive Psychology, Artificial Intelligence, Cognitive Neuroscience and Signal Processing, having authored 20 papers that have together received 469 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (7 papers), Emotion and Mood Recognition (5 papers), EEG and Brain-Computer Interfaces (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Machine Learning and Algorithms (3 papers), Machine Learning and Data Classification (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Hand Gesture Recognition Systems (3 papers). The work is most often cited by research in Artificial Intelligence (354 citations), Computer Vision and Pattern Recognition (174 citations), Human-Computer Interaction (13 citations), Media Technology (16 citations) and Cancer Research (26 citations). Rita Chattopadhyay has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include Sethuraman Panchanathan, Jieping Ye, Ian Davidson, Qian Sun, Wei Fan, Wei Fan, Qian Sun, Zheng Wang, Gaurav N. Pradhan and Zheng Wang. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Biomedical Engineering, IEEE Internet of Things Journal, Neural Information Processing Systems and PubMed.
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.