Thesis

  • Efficient Continual Learning and On-Device Training for Mobile and IoT Devices
    Young D. Kwon
    University of Cambridge Ph.D. Thesis, September 2024 | PDF | BibTex | Link

  • Geographical engagement and churn prediction in location-based social networks
    Young D. Kwon
    HKUST M.Phil. Thesis, January 2020 | PDF | BibTex | Link


Preprints

  • MetaCLBench: Meta Continual Learning Benchmark on Resource-Constrained Edge Devices
    Young D. Kwon*, Sijia Li*, Lik-Hang Lee, and Pan Hui
    arXiv 2025 | PDF | Link | * Co-first authors

  • LeanTTA: A Backpropagation-Free and Stateless Approach to Quantized Test-Time Adaptation on Edge Devices
    Cynthia Dong, Hong Jia, Young D. Kwon, Georgios Rizos, and Cecilia Mascolo
    arXiv 2025 | PDF | Link

  • HideNseek: Federated Lottery Ticket via Server-side Pruning and Sign Supermask
    Anish K. Vallapuram, Pengyuan Zhou, Young D. Kwon, Lik Hang Lee, Hengwei Xu, and Pan Hui
    arXiv 2022 | PDF | Link


Publications

  • TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
    Young D. Kwon, Rui Li, Stylianos I. Venieris, Jagmohan Chauhan, Nicholas D. Lane, and Cecilia Mascolo
    ICML 2024 | PDF | BibTex | Link
    Samsung Best Paper Silver Award 2024

  • TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
    Hong Jia, Young D. Kwon, Alessio Orsino, Ting Dang, Domenico Talia, and Cecilia Mascolo
    NeurIPS 2024 | PDF | Poster | Slides | BibTex | Link | Code

  • A Framework for On-Device Uncertainty-Aware Event Detection on Microcontrollers
    Hong Jia, Young D. Kwon, Dong Ma, Nhat Pham, Lorena Qendro, Tam Vu, and Cecilia Mascolo
    PMCJ 2024

  • UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers
    Hong Jia, Young D. Kwon, Dong Ma, Nhat Pham, Lorena Qendro, Tam Vu, and Cecilia Mascolo
    PerCom 2024 | PDF | BibTex
    Oral Presentation, Full Paper Acceptance Rate: 14.5%

  • LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms
    Young D. Kwon, Jagmohan Chauhan, Hong Jia, and Stylianos I. Venieris, and Cecilia Mascolo
    SenSys 2023 | PDF | BibTex
    Oral Presentation, Full Paper Acceptance Rate: 18.9%

  • ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions
    Reza Hadi Mogavi, Chao Deng, Justin Juho Kim, Pengyuan Zhou, Young D. Kwon, Ahmed Hosny Saleh Metwally, Ahmed Tlili, Simone Bassanelli, Antonio Bucchiarone, Sujit Gujar, Lennart E. Nacke, and Pan Hui
    Computers in Human Behavior: Artificial Humans 2023 | PDF | BibTex | Link

  • YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers
    Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
    IPSN 2022 | PDF | BibTex | Link

  • PROS: an Efficient Pattern-Driven Compressive Sensing Framework for Low-Power Biopotential-based Wearables with On-chip Intelligence
    Nhat Pham, Hong Jia, Minh Tran, Tuan Dinh, Nam Bui, Young D. Kwon, Dong Ma, VP Nguyen, Cecilia Mascolo, Tam Vu
    MobiCom 2022 | PDF | BibTex | Link
    Oral Presentation, Full Paper Acceptance Rate: 17.8%

  • Exploring On-Device Learning Using Few Shots for Audio Classification
    Jagmohan Chauhan, Young D. Kwon, and Cecilia Mascolo
    EUSIPCO 2022 | PDF | BibTex | Link

  • MyoKey: Inertial Motion Sensing and Gesture-based QWERTY Keyboard for Extended Realities
    Kirill A. Shatilov, Young D. Kwon, Lik-Hang Lee, Dimitris Chatzopoulos, and Pan Hui
    TMC 2022 | PDF | BibTex | Link

  • Causal Analysis on the Anchor Store Effect in a Location-based Social Network
    Anish Krishna Vallapuram, Young D. Kwon, Lik-Hang Lee, Fengli Xu, Pan Hui
    ASONAM 2022 | PDF | BibTex | Link

  • Enabling On-Device Smartphone GPU based Training: Lessons Learned
    Anish Das, Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
    PerFail (PerCom 2022 Workshop) | PDF | BibTex | Link

  • Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications
    Young D. Kwon, Jagmohan Chauhan, Abhishek Kumar, Pan Hui, and Cecilia Mascolo
    SEC 2021 | PDF | BibTex | Link
    Best Paper Award

  • Interpretable Business Survival Prediction
    Anish Krishna Vallapuram, Nikhil Nanda, Young D. Kwon, and Pan Hui
    ASONAM 2021 | PDF | BibTex | Link

  • IAN: Interpretable Attention Network for Churn Prediction in LBSNs
    Liang-Yu Chen, Yutong Chen, Young D. Kwon, Youwen Kang, and Pan Hui
    ASONAM 2021 | PDF | BibTex | Link

  • FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications
    Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
    Interspeech 2021 | PDF | BibTex | Link

  • Knowing when we do not know: Bayesian continual learning for sensing-based analysis tasks
    Sandra Servia Rodriguez, Cecilia Mascolo, and Young D. Kwon
    arXiv | PDF | BibTex | Link

  • ContAuth: Continual Learning Framework for Behavioral-based User Authentication
    Jagmohan Chauhan, Young D. Kwon, Pan Hui, and Cecilia Mascolo
    IMWUT/UbiComp 2021 | PDF | BibTex | Link

  • Aquilis: Using Contextual Integrity for Privacy Protection on Mobile Devices
    Abhishek Kumar, Tristan Braud, Young D. Kwon, and Pan Hui
    IMWUT/UbiComp 2021 | PDF | BibTex | Link

  • Enemy at the Gate: Evolution of Twitter User's Polarization During National Crisis
    Ehsan Ul Haq, Tristan Braud, Young D. Kwon, and Pan Hui
    ASONAM 2020 | PDF | BibTex

  • A Survey on Computational Politics
    Ehsan Ul Haq, Tristan Braud, Young D. Kwon, and Pan Hui.
    IEEE Access | PDF | BibTex | Link

  • MyoKey: Surface Electromyography and Inertial Motion Sensing-based Text Entry in AR
    Young D. Kwon, Kirill A. Shatilov, Lik-Hang Lee, Serkan Kumyol, Kit Yung Lam, Yui-Pan Yau, and Pan Hui
    PerCom 2020 WIP | PDF | Slides | BibTex | Link

  • GeoLifecycle: User Engagement of Geographical Exploration and Churn Prediction in LBSNs
    Young D. Kwon, Dimitris Chatzopoulos, Ehsan Ul Haq, Raymond Chi-Wing Wong, and Pan Hui.
    IMWUT/UbiComp 2019 | PDF | Slides | BibTex | Link

  • Effects of Ego Networks and Communities on Self-Disclosure in an Online Social Network
    Young D. Kwon, Reza Hadi Mogavi, Ehsan Ul Haq, Youngjin Kwon, Xiaojuan Ma, and Pan Hui
    ASONAM 2019 | PDF | Slides | BibTex | Link
    Oral Presentation, Full Paper Acceptance Rate: 14%

  • UbiComp/ISWC 2019: A Post-Conference Summary Report
    Young D. Kwon, Mohammed Khwaja, Neille-Ann H. Tan, Marla Narazani, Mikolaj P. Wozniak, Arshad Nasser, Rahul Majethia, Lucy Van Kleunen, Victoria Neumann, and Rajkarn Singh
    IEEE Pervasive Computing, 2019 (Impact Factor: 3.813) | PDF | BibTex | Link

  • Document Summarization Considering Entailment Relation between Sentences
    Youngdae Kwon, Noo-ri Kim, and Jee-Hyong Lee
    Journal of KIISE: Software and Application 2017 | Link

  • Document Summarization Considering Entailment Relation between Sentences
    Youngdae Kwon, Noo-ri Kim, and Jee-Hyong Lee
    Proceedings of the KIISE conference 2016 | Link
    Honorable Mention, and invited to Journal of KIISE

  • Method to Discover Novel Attribute Relationships using Social-Attribute Network in Google+
    Youngdae Kwon, Chung Kwan Tse, Chong Bor Hung, and Cheuk Man Chiu
    Proceedings of the KIISE conference 2015 | Link
    Honorable Mention for undergraduate students' papers


PhD Progress Reports and Manuscripts

  • Efficient Continual Learning and On-Device Training for Mobile and IoT Dvices
    Young D. Kwon
    University of Cambridge Ph.D. Third Year Report, Sep 2023 | PDF | BibTex

  • Efficient Meta Continual Learning on the Edge
    Young D. Kwon
    SEC '21 Ph.D. Forum, Dec 2021 | PDF | BibTex

  • Efficient On-device Systems that can Sense, Learn, and Optimize Continually in the Wild
    Young D. Kwon
    University of Cambridge Ph.D. First Year Report, June 2021 | PDF | BibTex

  • Characterization of Newcomers and Prediction of Potential Long-term Contributors in LBSNs
    Young D. Kwon, Dimitris Chatzopoulos, Ehsan Ul Haq, Huber Flores, Raymond Chi-Wing Wong, and Pan Hui.
    in progress


Research Experiences

Optimising DNN Processing on Extremely Resource-Limited Devices
Research Intern (Advisor: Dr. Stylianos I. Venieris, Dr. Rui Li, and Prof. Nicholas D. Lane ) · Apr. 2022 ~ Apr. 2023
• Participated in various projects related to optimising DNN processing on extremely resource-constrained devices

Incremental Learning on Resource-constrained Devices
Research Assistant (Advisor: Dr. Jagmohan Chauhan and Prof. Cecilia Mascolo ) · Jul. 2020 ~ Sep. 2020
• Participated in a project to apply incremental learning on resource-constrained devices

A Study of Applying Neural Networks on a Database
Research Assistant (Advisor: Prof. Dimitris Papadias ) · Feb. 2020 ~ Jun. 2020
• Participated in a project to apply neural networks on a database

Computer Laboratory at the University of Cambridge
Visiting Research Student (Advisor: Dr. Jagmohan Chauhan and Prof. Cecilia Mascolo ) · Jul. 2019 ~ Dec. 2019
• Investigated the Catastrophic Forgetting problem on mobile systems

User Engagement Analysis and Churn Prediction with LBSN Datasets
Postgraduate Research Stduent (Advisor: Prof. Raymond Wong and Prof. Pan Hui) · Aug. 2018 ~ Present
• Conducted a quantitative analysis to understand user engagement patterns exhibited both offline and online in LBSNs
• Examined the behavioral differences between churners and stayers among highly active users from various aspects; significantly improved the performance of churn prediction task over all baselines using our proposed features
• Paper accepted in the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp), 2019 as the first author
• Investigated a project of characterizing users and predicting potential long-term contributors in LBSNs

HKUST-DT System and Media Laboratory at HKUST
Postgraduate Research Stduent (Advisor: Prof. Pan Hui) · Aug. 2017 ~ Present
• Carried out my own project on users' self-disclosing behaviors in online social networks. The resulting paper was accepted in ASONAM 2019 as the first author
• Participated in a project of Ph.D. student Ehsan Ul Haq on inferring political leaning of users in a Q&A forum
• Involved in a project of Ph.D. student Reza Hadi Mogavi on predicting churning users in a Q&A forum

Information & Intelligence System Lab. at SKKU
Research Intern (Advisor: Prof. Jee-Hyong Lee) · Sep. 2015 - June. 2016
• Proposed a new algorithm, TextRank-NLI, which combines a Deep Learning based Natural Language Inference model and a Graph-based ranking algorithm used in a single document extraction-based summarization task
- Achieved Outstanding Undergraduate Final Year Project Award in the college of ICE
- Received Honorable Mention, and invited to the journal extension

Social Network Analysis Project with Social-Attribute Network Dataset of Google+
Undergraduate Research Student (Advisor: Prof. Pan Hui) · Feb. 2015 ~ June. 2015
• Researched to discover novel relationships using association rule mining with attributes of users in Google+ social-attribute networks
- Achieved Honorable Mention for undergraduate students' papers