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portfolio
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publications
CRL-MABA: A Completion Rate Learning-Based Accurate Data Collection Scheme in Large-Scale Energy Internet
Published in IEEE Internet of Things Journal, 2024
A data collection scheme using completion rate learning and MAB for Energy Internet environments.
Recommended citation: Fan, K., Tang, J., Xie, W., Han, F., et al. (2024). "CRL-MABA: A Completion Rate Learning-Based Accurate Data Collection Scheme in Large-Scale Energy Internet." IEEE IoT Journal, 11(14), 24400–24413.
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Q-BLPP: A Quality-Enabled Bilateral Location Privacy-Preserving Service Construction Scheme in Mobile Crowd Sensing
Published in IEEE Transactions on Services Computing, 2024
A bilateral location privacy-preserving scheme to construct high-quality services in mobile crowd sensing.
Recommended citation: Tang, J., Cai, Y., Long, S., Shen, Y., Fan, K., et al. (2024). "Q-BLPP: A Quality-Enabled Bilateral Location Privacy-Preserving Service Construction Scheme in Mobile Crowd Sensing." IEEE TSC, 17(6), 4151–4165.
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CPDZ: A Credibility-Aware and Privacy-Preserving Data Collection Scheme with Zero-Trust in Next-Generation Crowdsensing Networks
Published in IEEE Journal on Selected Areas in Communications, 2025
A zero-trust and privacy-preserving data collection scheme for next-generation crowdsensing systems.
Recommended citation: J. Tang et al., "CPDZ: A Credibility-Aware and Privacy-Preserving Data Collection Scheme with Zero-Trust in Next-Generation Crowdsensing Networks," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2025.3560038." IEEE JSAC.
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A Quality-Aware and Obfuscation-Based Data Collection Scheme for Cyber-Physical Metaverse Systems
Published in ACM Transactions on Multimedia Computing, Communications, and Applications, 2025
A novel task privacy-preserving and quality-aware data collection scheme for cyber-physical metaverse systems.
Recommended citation: Tang, J., Fan, K., Yin, W., Yang, S., et al. (2025). "A Quality-Aware and Obfuscation-Based Data Collection Scheme for Cyber-Physical Metaverse Systems." ACM TOMM, 21(2), Article 50.
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RMDF-CV: A Reliable Multi-Source Data Fusion Scheme With Cross Validation for Quality Service Construction in Mobile Crowd Sensing
Published in IEEE Transactions on Services Computing, 2025
A data fusion scheme with cross-validation to enhance reliability in mobile crowd sensing.
Recommended citation: Fan, K., Guo, J., Li, R., Li, Y., et al. (2025). "RMDF-CV: A Reliable Multi-Source Data Fusion Scheme With Cross Validation for Quality Service Construction in Mobile Crowd Sensing." IEEE TSC, 18(1), 399–413.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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