Lorena Qendro
Impact in
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- Advanced Neural Network Applications
- Context-Aware Activity Recognition Systems
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- IoT and Edge/Fog Computing
- Age of Information Optimization
Papers in
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- Adversarial Robustness in Machine Learning 2
- Anomaly Detection Techniques and Applications 2
- Imbalanced Data Classification Techniques 1
- Machine Learning and Algorithms 1
- Co-authors
- Petko Georgiev (2 shared papers)Nicholas D. Lane (2 shared papers)Fahim Kawsar (3 shared papers)Sourav Bhattacharya (1 shared paper)Lei Jiao (1 shared paper)Claudio Forlivesi (1 shared paper)Cecilia Mascolo (8 shared papers)Alessandro Montanari (1 shared paper)
- Journals
- IEEE Journal of Biomedical and Health Informatics (1 paper)IEEE Pervasive Computing (1 paper)ORCA Online Research @Cardiff (Cardiff University) (1 paper)Apollo (University of Cambridge) (1 paper)PubMed (1 paper)
- Partner nations
- United KingdomUnited StatesSingapore
In The Last Decade
Lorena Qendro
11 papers receiving 576 citations
Lorena Qendro's Hit Papers
Peers
Comparison fields: 5 of 78
- Computer Vision and Pattern Recognition 331
- Computer Networks and Communications 207
- Signal Processing 83
- Artificial Intelligence 193
- Hardware and Architecture 40
Countries citing papers authored by Lorena Qendro
This map shows the geographic impact of Lorena Qendro'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 Lorena Qendro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lorena Qendro more than expected).
Fields of papers citing papers by Lorena Qendro
This network shows the impact of papers produced by Lorena Qendro. 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 Lorena Qendro. The network helps show where Lorena Qendro may publish in the future.
Co-authors
The 18 scholars most cited alongside Lorena Qendro, 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 | DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices Hit paper breakdown → | 2016 | 295 |
| 2 | 2015 | 225 | |
| 3 | 2020 | 30 | |
| 4 | 2021 | 16 | |
| 5 | 2024 | 6 | |
| 6 | 2022 | 6 | |
| 7 | 2024 | 4 | |
| 8 | 2022 | 2 | |
| 9 | 2021 | 2 | |
| 10 | 2022 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2023 | 0 |
About Lorena Qendro
Lorena Qendro is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Electrical and Electronic Engineering, having authored 12 papers that have together received 588 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (2 papers), Music and Audio Processing (2 papers), Adversarial Robustness in Machine Learning (2 papers), Anomaly Detection Techniques and Applications (2 papers), COVID-19 diagnosis using AI (1 paper), Imbalanced Data Classification Techniques (1 paper), Interactive and Immersive Displays (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (331 citations), Computer Networks and Communications (207 citations), Signal Processing (83 citations), Artificial Intelligence (193 citations) and Hardware and Architecture (40 citations). Lorena Qendro has collaborated with scholars based in United Kingdom, United States and Singapore. Frequent co-authors include Petko Georgiev, Nicholas D. Lane, Fahim Kawsar, Sourav Bhattacharya, Lei Jiao, Claudio Forlivesi, Cecilia Mascolo, Alessandro Montanari, Jing Han and Xia Tong. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, IEEE Pervasive Computing, ORCA Online Research @Cardiff (Cardiff University), Apollo (University of Cambridge) 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.