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
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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
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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
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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
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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
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YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers
Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
IPSN 2022
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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
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Exploring On-Device Learning Using Few Shots for Audio Classification
Jagmohan Chauhan, Young D. Kwon, and Cecilia Mascolo
EUSIPCO 2022
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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
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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
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Enabling On-Device Smartphone GPU based Training: Lessons Learned
Anish Das, Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
PerFail (PerCom 2022 Workshop)
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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
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Interpretable Business Survival Prediction
Anish Krishna Vallapuram, Nikhil Nanda, Young D. Kwon, and Pan Hui
ASONAM 2021
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IAN: Interpretable Attention Network for Churn Prediction in LBSNs
Liang-Yu Chen, Yutong Chen, Young D. Kwon, Youwen Kang, and Pan Hui
ASONAM 2021
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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
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Knowing when we do not know: Bayesian continual learning for sensing-based analysis tasks
Sandra Servia Rodriguez, Cecilia Mascolo, and Young D. Kwon
arXiv
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ContAuth: Continual Learning Framework for Behavioral-based User Authentication
Jagmohan Chauhan, Young D. Kwon, Pan Hui, and Cecilia Mascolo
IMWUT/UbiComp 2021
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Aquilis: Using Contextual Integrity for Privacy Protection on Mobile Devices
Abhishek Kumar, Tristan Braud, Young D. Kwon, and Pan Hui
IMWUT/UbiComp 2021
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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
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A Survey on Computational Politics
Ehsan Ul Haq, Tristan Braud, Young D. Kwon, and Pan Hui.
IEEE Access
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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
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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
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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
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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)
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Document Summarization Considering Entailment Relation between Sentences
Youngdae Kwon, Noo-ri Kim, and Jee-Hyong Lee
Journal of KIISE: Software and Application 2017
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Document Summarization Considering Entailment Relation between Sentences
Youngdae Kwon, Noo-ri Kim, and Jee-Hyong Lee
Proceedings of the KIISE conference 2016
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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
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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
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Efficient Meta Continual Learning on the Edge
Young D. Kwon
SEC '21 Ph.D. Forum, Dec 2021
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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
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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
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
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