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Department of Computer Science and Technology

  • PhD Student

Biography

Young Kwon is a Ph.D. student majoring in Computer Science in the Mobile Systems Group at the University of Cambridge, where he is supervised by Prof. Cecilia Mascolo and funded by Nokia Bell Labs.
 
His research focuses on resource-constrained mobile systems to enable context-aware adaptation to the changing environments (e.g., new inputs and users) in real-time while preserving privacy. To this end, He leverages computational methods from continual learning, machine learning, and network science.
 
For more details, please visit his personal website (Link)

Publications

Journal articles

  • Shatilov, KA., Kwon, YD., Lee, LH., Chatzopoulos, D. and Hui, P., 2023. MyoKey: Inertial Motion Sensing and Gesture-Based QWERTY Keyboard for Extended Realities IEEE Transactions on Mobile Computing, v. 22
    Doi: 10.1109/TMC.2022.3156939
  • Kwon, YD., Chauhan, J., Kumar, A., Hkust, PH. and Mascolo, C., 2021. Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications 6th ACM/IEEE Symposium on Edge Computing, SEC 2021,
    Doi: http://doi.org/10.1145/3453142.3491285
  • Ul Haq, E., Braud, T., Kwon, YD. and Hui, P., 2020. A survey on computational politics IEEE Access, v. 8
    Doi: http://doi.org/10.1109/ACCESS.2020.3034983
  • Chauhan, J., Kwon, YD., Hui, P. and Mascolo, C., 2020. ContAuth: Continual Learning Framework for Behavioral-based User Authentication Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, v. 4
    Doi: http://doi.org/10.1145/3432203
  • Kumar, A., Braud, T., Kwon, YD. and Hui, P., 2020. Aquilis: Using contextual integrity for privacy protection on mobile devices Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, v. 4
    Doi: 10.1145/3432205
  • Conference proceedings

  • Vallapuram, AK., Kwon, YD., Lee, LH., Xu, F. and Hui, P., 2022. Causal Analysis on the Anchor Store Effect in a Location-based Social Network Proceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022,
    Doi: http://doi.org/10.1109/ASONAM55673.2022.10068687
  • Das, A., Kwon, YD., Chauhan, J. and Mascolo, C., 2022. Enabling On-Device Smartphone GPU based Training: Lessons Learned 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2022,
    Doi: 10.1109/PerComWorkshops53856.2022.9767442
  • Pham, N., Jia, H., Tran, M., Dinh, T., Bui, N., Kwon, Y., Ma, D., Nguyen, P., Mascolo, C. and Vu, T., 2022. PROS: An Efficient Pattern-Driven Compressive Sensing Framework for Low-Power Biopotential-basedWearables with On-chip Intelligence Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM,
    Doi: http://doi.org/10.1145/3495243.3560533
  • Kwon, YD., Chauhan, J. and Mascolo, C., 2022. YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers Proceedings - 21st ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2022,
    Doi: http://doi.org/10.1109/IPSN54338.2022.00030
  • Chauhan, J., Kwon, YD. and Mascolo, C., 2022. Exploring On-Device Learning Using Few Shots for Audio Classification European Signal Processing Conference, v. 2022-August
  • Chen, L-Y., Chen, Y., Kwon, YD., Kang, Y. and Hui, P., 2021. IAN: interpretable attention network for churn prediction in LBSNs Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining,
    Doi: http://doi.org/10.1145/3487351.3488328
  • Kwon, YD., Chauhan, J., Kumar, A., Hui, P. and Mascolo, C., 2021. Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications 2021 IEEE/ACM Symposium on Edge Computing (SEC),
    Doi: 10.1145/3453142.3491285
  • Haq, EU., Braud, T., Kwon, YD. and Hui, P., 2020. Enemy at the Gate: Evolution of Twitter User's Polarization during National Crisis Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020,
    Doi: http://doi.org/10.1109/ASONAM49781.2020.9381296
  • Kwon, YD., Shatilov, KA., Lee, LH., Kumyol, S., Lam, KY., Yau, YP. and Hui, P., 2020. MyoKey: Surface Electromyography and Inertial Motion Sensing-based Text Entry in AR 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020,
    Doi: http://doi.org/10.1109/PerComWorkshops48775.2020.9156084
  • Kwon, YD., Mogavi, RH., Ul Haq, E., Kwon, Y., Ma, X. and Hui, P., 2019. Effects of ego networks and communities on self-disclosure in an online social network Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019,
    Doi: http://doi.org/10.1145/3341161.3342881
  • Kwon, YD., Singh, R., Khwaja, M., Tan, NAH., Narazani, M., Wozniak, MP., Nasser, A., Majethia, R., Van Kleunen, L. and Neumann, V., 2019. UbiComp/ISWC 2019: A Post-Conference Summary Report IEEE Pervasive Computing, v. 18
    Doi: http://doi.org/10.1109/MPRV.2019.2947953
  • Kwon, YD., Chauhan, J. and Mascolo, C., FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications Proc. Interspeech 2021,
    Doi: 10.21437/Interspeech.2021-1091
  • Vallapuram, AK., Nanda, N., Kwon, YD. and Hui, P., Interpretable business survival prediction Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining,
    Doi: http://doi.org/10.1145/3487351.3488353
  • Kwon, YD., Chauhan, J. and Mascolo, C., YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers
  • Kwon, YD., Chauhan, J., Jia, H., Venieris, SI. and Mascolo, C., LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms
    Doi: http://doi.org/10.1145/3625687.3625804
  • Contact Details

    Room: 
    FN01
    Email: 

    ydk21@cam.ac.uk