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Chenxi Qiu

Title: Assistant Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Clemson University, 2015
    Major: Computer Engineering
  • BS, Xidian University, 2009
    Major: Telecommunication Engineering

Current Scheduled Teaching

CSCE 5580.002Computer NetworksSpring 2025
CSCE 5580.004Computer NetworksFall 2024
CSCE 6950.825Doctoral DissertationFall 2024
CSCE 6940.825Individual ResearchFall 2024

Previous Scheduled Teaching

CSCE 6950.925Doctoral DissertationSummer 10W 2024
CSCE 5580.002Computer NetworksSpring 2024 SPOT
CSCE 6950.925Doctoral DissertationSpring 2024
CSCE 6940.925Individual ResearchSpring 2024
CSCE 5580.004Computer NetworksFall 2023 SPOT
CSCE 6940.825Individual ResearchFall 2023
CSCE 5580.002Computer NetworksSpring 2023 SPOT
CSCE 6940.918Individual ResearchSpring 2023
CSCE 5580.004Computer NetworksFall 2022 Syllabus SPOT
CSCE 6940.825Individual ResearchFall 2022
CSCE 5580.001Computer NetworksSpring 2022 SPOT
CSCE 6940.918Individual ResearchSpring 2022
CSCE 2100.001Foundations of ComputingFall 2021 Syllabus SPOT
CSCE 2100.201Foundations of ComputingFall 2021 Syllabus SPOT
CSCE 2100.210Foundations of ComputingFall 2021 Syllabus SPOT

Published Intellectual Contributions

    Conference Proceeding

  • Yadav, S., Le, T., Dong, S., Fan, H., Yang, Q., Qiu, C., Li, X., Huang, Y. A New Simulation Platform For Learning-Empowered Distributed Sensing. SPIE Defense + Commercial Sensing 2024.
  • Qiu, C., Yadav, S., Ji, Y., Squicciarini, A., Dantu, R., Zhao, J., Xu, C. Fine-Grained Geo-Obfuscation to Protect Workers’ Location Privacy in Large-Scale Time-Sensitive Spatial Crowdsourcing. 27th International Conference on Extending Database Technology (EDBT) 2024.
  • Jia, F., Qiu, C., Rajtmajer, S., Squicciarini, A. Content Promotion in Networked Disclosure Game. Conference on Uncertainty in Artificial Intelligence (UAI) 2023.
  • Pappachan, P., Qiu, C., Squicciarini, A., Manjunath, V. User Customizable and Robust Geo-Indistinguishability for Location Privacy. International Conference on Extending Database Technology (EDBT) 2023.
  • Pappachan, P., Hunsur Manjunath , V., Qiu, C., Squicciarini, A., Onweller, H. CORGI: An interactive framework for Customizable and Robust Location Obfuscation. IEEE International Conference on Data Engineering (ICDE) Demo 2023.
  • Qiu, C., Yan, L., Squicciarini, A., Zhao, J., Xu, C., Pappachan, P. TrafficAdaptor: An Adaptive Obfuscation Strategy for Vehicle Location Privacy Against Vehicle Traffic Flow Aware Attacks. Proceedings of ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL) 2022.
  • Qiu, C., Yadav, S., Squicciarini, A., Yang, Q., Fu, S., Zhao, J., Xu, C. Distributed Data-Sharing Consensus in Cooperative Perception of Autonomous Vehicles. Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS) 2022.
  • Journal Article

  • Sarker, A., Shen, H., Qiu, C., Uehara, H., Zhang, K. (2023). Brake Signal-based Driver’s Location Tracking in Usage-based Auto Insurance Programs. IEEE Internet of Things Journal.
  • Yan, L., Shen, H., Zhao, J., Xu, C., Luo, F., Qiu, C., Zhang, Z., Mahmud, S. (2021). CatCharger: Deploying In-motion Wireless Chargers in a Metropolitan Road Network via Categorization and Clustering of Vehicle Traffic. IEEE Internet of Things Journal.
  • Wu, B., Tang, Y., Qiu, C., Huang, Y., Huang, C., Prucnal, P. (2021). Secure Analysis of Optical Steganography With Spectral Signature Measurement. IEEE Photonics Technology Letters. 33 (17) 971 - 974.
  • Shen, H., Qiu, C. (2021). Scheduling Inter-Datacenter Video Flows for Cost Efficiency. IEEE Transactions on Services Computing. 14 (3) 834 - 849.
  • Wu, B., Yang, Q., Qiu, C., Tang, Y. (2021). Wideband Anti-Jamming Based on Free Space Optical Communication and Photonic Signal Processing. Sensors. 21 (4) 12. MDPI.
  • Wang, N., Li, J., Ho, S., Qiu, C. (2021). Distributed machine learning for energy trading in electric distribution system of the future. 34 (1) Elsevier.

Contracts, Grants and Sponsored Research

    Grant - Research

  • Qiu, C. (Principal), "Customizable Geo-Obfuscation to Protect Users' Location Privacy in Mobile Crowdsourcing," sponsored by NSF, Federal, $344997 Funded. (2023 - 2026).
  • Huang, Y. (Principal), Li, X. (Co-Principal), Yang, Q. (Co-Principal), Fan, H. (Co-Principal), Qiu, C. (Co-Principal), Wei, Y. (Co-Principal), Baba, A.I. (Supporting), "Intelligent Distributed Sensing," sponsored by Army Research Lab/Northeastern University, Federal, $902266 Funded. (2024 - 2025).
  • Huang, Y. (Principal), Li, X. (Co-Principal), Yang, Q. (Co-Principal), Fan, H. (Co-Principal), Qiu, C. (Co-Principal), Wei, Y. (Co-Principal), Baba, A.I. (Supporting), "Learning Empowered Distributed Sensing," sponsored by Army Research Lab/Northeastern University, Federal, $2069324 Funded. (2023 - 2024).
  • Qiu, C. (Principal), "Privacy protection of Vehicles location in Spatial Crowdsourcing under realistic adversarial models," sponsored by NSF, National, $243107 Funded. (2021 - 2023).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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