Sara Khalifa

2.0k total citations · 1 hit paper
36 papers, 1.2k citations indexed

About

Sara Khalifa is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Sara Khalifa has authored 36 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 15 papers in Computer Vision and Pattern Recognition and 12 papers in Mechanical Engineering. Recurrent topics in Sara Khalifa's work include Context-Aware Activity Recognition Systems (13 papers), Innovative Energy Harvesting Technologies (12 papers) and Energy Harvesting in Wireless Networks (11 papers). Sara Khalifa is often cited by papers focused on Context-Aware Activity Recognition Systems (13 papers), Innovative Energy Harvesting Technologies (12 papers) and Energy Harvesting in Wireless Networks (11 papers). Sara Khalifa collaborates with scholars based in Australia, Germany and United Kingdom. Sara Khalifa's co-authors include Mahbub Hassan, Aruna Seneviratne, Guohao Lan, Yining Hu, Suranga Seneviratne, Kanchana Thilakarathna, Tham Nguyen, Raja Jurdak, Sajal K. Das and Rajib Rana and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Communications Surveys & Tutorials.

In The Last Decade

Sara Khalifa

33 papers receiving 1.2k citations

Hit Papers

A Survey of Wearable Devices and Challenges 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sara Khalifa Australia 17 492 400 332 256 204 36 1.2k
Guohao Lan Australia 16 490 1.0× 429 1.1× 351 1.1× 295 1.2× 195 1.0× 44 1.2k
Yasar Amin Pakistan 28 1.8k 3.7× 563 1.4× 186 0.6× 263 1.0× 123 0.6× 172 2.7k
Chao Cai China 19 489 1.0× 296 0.7× 225 0.7× 285 1.1× 84 0.4× 84 1.3k
Jean-Yves Fourniols France 9 268 0.5× 347 0.9× 334 1.0× 227 0.9× 52 0.3× 30 1.2k
Suranga Seneviratne Australia 16 318 0.6× 303 0.8× 251 0.8× 413 1.6× 43 0.2× 60 1.4k
Kanchana Thilakarathna Australia 12 245 0.5× 227 0.6× 329 1.0× 373 1.5× 41 0.2× 63 1.3k
Lei Xie China 27 1.1k 2.3× 246 0.6× 367 1.1× 496 1.9× 84 0.4× 183 2.3k
Bo Cheng China 25 878 1.8× 287 0.7× 184 0.6× 296 1.2× 189 0.9× 90 2.0k
Yining Hu Australia 8 219 0.4× 271 0.7× 164 0.5× 256 1.0× 40 0.2× 20 956

Countries citing papers authored by Sara Khalifa

Since Specialization
Citations

This map shows the geographic impact of Sara Khalifa'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 Sara Khalifa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Khalifa more than expected).

Fields of papers citing papers by Sara Khalifa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara Khalifa. 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 Sara Khalifa. The network helps show where Sara Khalifa may publish in the future.

Co-authorship network of co-authors of Sara Khalifa

This figure shows the co-authorship network connecting the top 25 collaborators of Sara Khalifa. A scholar is included among the top collaborators of Sara Khalifa 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 Sara Khalifa. Sara Khalifa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rana, Rajib, et al.. (2025). Representation learning with parameterised quantum circuits for advancing speech emotion recognition. Scientific Reports. 15(1). 44353–44353. 1 indexed citations
2.
Sharma, Renuka, et al.. (2025). SensorGPT: A New Paradigm for Synthetic Sensory Data Generation. 176–182.
3.
Khalifa, Sara, et al.. (2025). VEH-Attack: Stealthy Tracking of Train Passengers With Side-Channel Attack on Vibration Energy Harvesting Wearables. IEEE Transactions on Intelligent Transportation Systems. 26(7). 9669–9681.
4.
Pal, Shantanu, Sara Khalifa, Volkan Dedeoglu, et al.. (2024). Uncertainty propagation in the internet of things. SHILAP Revista de lepidopterología. 4(1).
5.
Rana, Rajib, et al.. (2024). Domain Adapting Deep Reinforcement Learning for Real-World Speech Emotion Recognition. IEEE Access. 12. 193101–193114. 2 indexed citations
6.
Sandhu, Muhammad Moid, Sara Khalifa, Marius Portmann, & Raja Jurdak. (2023). Self-Powered Internet of Things. Green energy and technology. 1 indexed citations
7.
Sandhu, Muhammad Moid, et al.. (2023). FusedAR: Energy-Positive Human Activity Recognition Using Kinetic and Solar Signal Fusion. IEEE Sensors Journal. 23(11). 12411–12426. 9 indexed citations
8.
Sandhu, Muhammad Moid, et al.. (2021). SolAR: Energy Positive Human Activity Recognition using Solar Cells. 1–10. 16 indexed citations
9.
Rana, Rajib, Siddique Latif, Sara Khalifa, Raja Jurdak, & Julien Epps. (2019). Multi-Task Semi-Supervised Adversarial Autoencoding for Speech Emotion. arXiv (Cornell University). 1 indexed citations
10.
Seneviratne, Suranga, Yining Hu, Tham Nguyen, et al.. (2017). A Survey of Wearable Devices and Challenges. IEEE Communications Surveys & Tutorials. 19(4). 2573–2620. 515 indexed citations breakdown →
11.
Lan, Guohao, Weitao Xu, Sara Khalifa, Mahbub Hassan, & Wen Hu. (2017). VEH-COM: Demodulating vibration energy harvesting for short range communication. 170–179. 11 indexed citations
12.
Khalifa, Sara, Guohao Lan, Mahbub Hassan, Aruna Seneviratne, & Sajal K. Das. (2017). HARKE: Human Activity Recognition from Kinetic Energy Harvesting Data in Wearable Devices. IEEE Transactions on Mobile Computing. 17(6). 1353–1368. 111 indexed citations
13.
Khalifa, Sara. (2016). Energy-efficient human activity recognition for self-powered wearable devices. Proceedings of the Australasian Computer Science Week Multiconference. 1–2. 2 indexed citations
14.
Khalifa, Sara, Guohao Lan, Mahbub Hassan, & Wen Hu. (2016). A Bayesian framework for energy-neutral activity monitoring with self-powered wearable sensors. UNSWorks (UNSW Sydney). 2. 1–6. 3 indexed citations
15.
Lan, Guohao, Sara Khalifa, Mahbub Hassan, & Wen Hu. (2015). Estimating Calorie Expenditure from Output Voltage of Piezoelectric Energy Harvester - an Experimental Feasibility Study. EAI Endorsed Transactions on Pervasive Health and Technology. 2(7). 1 indexed citations
16.
Lan, Guohao, Sara Khalifa, Mahbub Hassan, & Wen Hu. (2015). Estimating Calorie Expenditure from Output Voltage of Piezoelectric Energy Harvester - an Experimental Feasibility Study. SHILAP Revista de lepidopterología. 2(7). e4–e4. 14 indexed citations
17.
Khalifa, Sara, Mahbub Hassan, & Aruna Seneviratne. (2015). Pervasive self-powered human activity recognition without the accelerometer. UNSWorks (UNSW Sydney). 41 indexed citations
18.
Khalifa, Sara, Mahbub Hassan, & Aruna Seneviratne. (2015). Step Detection from Power Generation Pattern in Energy-Harvesting Wearable Devices. UNSWorks (UNSW Sydney). 604–610. 10 indexed citations
19.
Khalifa, Sara, Mahbub Hassan, & Aruna Seneviratne. (2014). Feature selection for floor-changing activity recognition in multi-floor pedestrian navigation. 21. 1–6. 10 indexed citations
20.
Khalifa, Sara, Mahbub Hassan, & Aruna Seneviratne. (2013). Adaptive pedestrian activity classification for indoor dead reckoning systems. 21. 1–7. 22 indexed citations

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.

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