Giulia Da Poian
- Cardiology and Cardiovascular Medicine top 5%
- Biomedical Engineering top 10%
- Cognitive Neuroscience top 10%
- Signal Processing top 10%
- Physiology
- Co-authors
- R. RinaldoRiccardo BernardiniGari D. CliffordAmit ShahChengyu LiuWalter KarlenQiao LiShamim Nemati
- Topics
- ECG Monitoring and Analysis (9 papers)EEG and Brain-Computer Interfaces (8 papers)Non-Invasive Vital Sign Monitoring (7 papers)
- Partner nations
- SwitzerlandUnited StatesItaly
In The Last Decade
Giulia Da Poian
26 papers receiving 606 citations
Peers
Comparison fields: 5 of 86
- Cardiology and Cardiovascular Medicine 361
- Biomedical Engineering 295
- Cognitive Neuroscience 184
- Signal Processing 97
- Physiology 65
Countries citing papers authored by Giulia Da Poian
This map shows the geographic impact of Giulia Da Poian'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 Giulia Da Poian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giulia Da Poian more than expected).
Fields of papers citing papers by Giulia Da Poian
This network shows the impact of papers produced by Giulia Da Poian. 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 Giulia Da Poian. The network helps show where Giulia Da Poian may publish in the future.
Co-authorship network of co-authors of Giulia Da Poian
This figure shows the co-authorship network connecting the top 25 collaborators of Giulia Da Poian. A scholar is included among the top collaborators of Giulia Da Poian 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 Giulia Da Poian. Giulia Da Poian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 11 | |
| 5 | 17 | |
| 6 | 9 | |
| 7 | 7 | |
| 8 | 17 | |
| 9 | 33 | |
| 10 | Two will do: Convolutional neural network with asymmetric loss, self-learning label correction, and hand-crafted features for imbalanced multi-label ECG data classification | 1 |
| 11 | 10 | |
| 12 | 10 | |
| 13 | 7 | |
| 14 | 185 | |
| 15 | 18 | |
| 16 | 6 | |
| 17 | 18 | |
| 18 | 48 | |
| 19 | 2 | |
| 20 | 82 |
About Giulia Da Poian
Giulia Da Poian is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Signal Processing, having authored 26 papers that have together received 619 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (9 papers), EEG and Brain-Computer Interfaces (8 papers) and Non-Invasive Vital Sign Monitoring (7 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (361 citations), Cognitive Neuroscience (184 citations) and Signal Processing (97 citations). Giulia Da Poian has collaborated with scholars based in Switzerland, United States and Italy. Frequent co-authors include R. Rinaldo, Riccardo Bernardini, Gari D. Clifford, Amit Shah, Chengyu Liu, Walter Karlen, Qiao Li, Shamim Nemati, Adriana Nicholson Vest and Christopher J. Rozell. Their work appears in journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and Sensors.
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.