I am a Research Scientist at Samsung AI Center-Cambridge and a doctoral candidate in Computer Science at the University of Cambridge. I am fortunate to work with Dr. Sourav Bhattacharya and Prof. Cecilia Mascolo.
I am passionate about drastically optimising On-device AI processing via algorithm & system innovations, enabling various and exciting real-world applications for users, thereby pushing the boundaries of what's possible within strict hardware constraints.
To this end, I develop new methods and systems and leverage knowledge from On-Device Machine Learning, Continual Learning, and Multi-Task Learning.
Want to Collaborate?
If you're interested in working with me, please contact me so we can have a chat.
I always love to interact and collaborate with brilliant minds.
News & Travel
- Sep, 2024 Our paper "TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices" is accepted by NeurIPS 2024 [Paper]
- Aug, 2024 Our team's recent research effort has been commercialised with On-device AI Wallpaper enabled on Samsung AI phone series: Galaxy S24, Z Flip 6 and Fold 6! [AI Product]
- Jul, 2024 I will attend ICML 2024 to present our paper "TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge". See you all in Vienna, Austria! [Talk]
- May, 2024 Our paper "TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge" is accepted by ICML 2024 (Accpetance Rate: 27.5%) [Paper]
- Mar, 2024 I presented our paper "UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers" on behalf of 1st author, Hong, at IEEE PerCom 2024 [Talk]
- Feb, 2024 I have been invited to give a talk regarding Efficient Continual and On-Device Learning for Edge Computing Platforms at EfficientML Reading Group [Talk]
- Dec, 2023 Our paper "UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers" is accepted to PerCom 2024 (Accpetance Rate: 14.5%) [Paper]
- Nov, 2023 Our paper "ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions" is accepted to Computers in Human Behavior: Artificial Humans 2023 [Paper]
- Nov, 2023 I presented 2 talks regarding data-and memory-efficient continual learning and on-device training at the extreme edge at SenSys 2023 [Talk]
- Oct, 2023 Our paper "LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms" is accepted to SenSys 2023 (Accpetance Rate: 18.9%) [Paper]
- Sep, 2023 I embarked on a new chapter in my journey after (almost) completing my PhD: I joined Samsung AI as a Research Scientist. [Job]
- Aug, 2023 I am happy to serve as Artifact Evaluation Committee for MobiCom 2023
- Mar, 2022 I have been invited to give a talk, "Deep Learning at the Extreme Edge", at Cambridge Korea Academic Society (CKAS) [Talk]
- Sep, 2022 Our paper "Causal Analysis on the Anchor Store Effect in a Location-based Social Network" is accepted to ASONAM 2022 [Paper]
- Aug, 2022 Our paper "PROS: an Efficient Pattern-Driven Compressive Sensing Framework for Low-Power Biopotential-based Wearables with On-chip Intelligence" is accepted to MobiCom 2022 [Paper]
- Jun, 2022 I plan to attend and present my recent work regarding efficient continual learning in mobile computing in MobiUK 2022 at UCL on 4-5th July. See you all soon there! [Talk]
- May, 2022 I am invited to serve as a Shadow PC member for ACM SenSys 2022
- May, 2022 Our paper "Exploring On-Device Learning Using Few Shots for Audio Classification" is accepted to EUSIPCO 2022 [Paper]
- April, 2022 I started a research internship at Samsung AI Center-Cambridge focusing on optimising DNN processing on microcontrollers.
- Feb, 2022 Our paper "MyoKey: Inertial Motion Sensing and Gesture-based QWERTY Keyboard for Extended Realities" is accepted to TMC [Paper]
- Feb, 2022 I have been invited to give a talk about YONO (our recent IPSN paper) at KMA [Talk]
- Jan, 2022 I have been invited to give 2 talks regarding on-device continual leanring and multi-task learning on heterogeneous DNNs at KAIST [Talk]
- Jan, 2022 I visited Prof. Lik-Hang Lee's ARM LAB at KAIST for a month
- Jan, 2022 Our paper "YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers" is accepted to IPSN 2022 [Paper]
- Jan, 2022 Mentored students' paper "Enabling On-Device Smartphone GPU based Training: Lessons Learned" is accepted to PerFail 2022, co-located with PerCom 2022. Congrats Anish Das [Paper]
- Dec, 2021 Our paper "Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications" won the Best Paper Award at SEC 2021
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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 -
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 | BibTex | Link -
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 | BibTexOral 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 | BibTexOral 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 | LinkOral 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 | LinkBest 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 | LinkContAuth: Continual Learning Framework for Behavioral-based User Authentication
Jagmohan Chauhan, Young D. Kwon, Pan Hui, and Cecilia Mascolo
IMWUT/UbiComp 2021 | PDF | BibTex | LinkAquilis: Using Contextual Integrity for Privacy Protection on Mobile Devices
Abhishek Kumar, Tristan Braud, Young D. Kwon, and Pan Hui
IMWUT/UbiComp 2021 | PDF | BibTex | LinkEnemy 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 | BibTexA Survey on Computational Politics
Ehsan Ul Haq, Tristan Braud, Young D. Kwon, and Pan Hui.
IEEE Access | PDF | BibTex | LinkMyoKey: 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 | LinkGeoLifecycle: 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 | LinkEffects 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 | LinkOral 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
Samsung AI Center-Cambridge
Research Scientist
· Sep. 2023 ~ Present
Advisor: Dr. Sourav Bhattacharya
Research Intern
· Apr. 2022 ~ Apr. 2023
Advisor: Dr. Stylianos I. Venieris, Dr. Rui Li, Prof. Nicholas D. Lane
Computer Laboratory, University of Cambridge
ML Developer
· Jul. 2020 ~ Sep. 2020
Advisor: Dr. Jagmohan Chauhan and Prof. Cecilia Mascolo
Dept. of CSE, HKUST
Research Assistant
· Mar. 2020 ~ Jun. 2020
Advisor: Prof. Dimitris Papadias
Memory Business, Samsung Electronics
Engineer
· Jul. 2016 ~ Aug. 2017
Engineering Intern
· Jul. 2015 ~ Aug. 2015
1st Fighter Wing, Republic of Korea Air Force
Staff Sergeant
· Feb. 2011 ~ Feb. 2013
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
Incremental Learning on Resource-constrained Devices
Research Assistant (Advisor: Dr. Jagmohan Chauhan and Prof. Cecilia Mascolo
) · Jul. 2020 ~ Sep. 2020
A Study of Applying Neural Networks on a Database
Research Assistant (Advisor:
Prof. Dimitris Papadias
) · Feb. 2020 ~ Jun. 2020
Computer Laboratory at the University of Cambridge
Visiting Research Student (Advisor:
Dr. Jagmohan Chauhan and Prof. Cecilia Mascolo
) · Jul. 2019 ~ Dec. 2019
User Engagement Analysis and Churn Prediction with LBSN Datasets
Postgraduate Research Stduent (Advisor:
Prof. Raymond Wong
and Prof. Pan Hui) · Aug. 2018 ~ Present
HKUST-DT System and Media Laboratory at HKUST
Postgraduate Research Stduent (Advisor: Prof. Pan Hui) · Aug. 2017 ~ Present
Information & Intelligence System Lab. at SKKU
Research Intern (Advisor: Prof. Jee-Hyong Lee) · Sep. 2015 - June. 2016
Social Network Analysis Project with Social-Attribute Network Dataset of Google+
Undergraduate Research Student (Advisor: Prof. Pan Hui) · Feb. 2015 ~ June. 2015
Mentorship
- • Anish Krishna Vallapuram (HKUST, now at Amazon)
- • Nikhil Nanda (Previously at HKUST, now at Columbia University)
- • Liang-yu Chen (Previously at HKUST, now at Purdue University)
- • Yutong Chen (Previously at HKUST, now at the University of Chicago)
- • Youwen Kang (Previously at HKUST, now at Tencent)
- • Anish Das (University of Cambridge, now at Goldman Sachs)
- • Nav Leelarathna (University of Cambridge)
- • Issam Nedjai (University of Cambridge)
- • Cynthia X. Dong (University of Cambridge)
Teaching Assistant
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Michaelmas 2022
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Michaelmas 2021
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Lent 2021
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Michaelmas 2020
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Spring 2020
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Spring 2019
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Fall 2018
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Spring 2018
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Spring 2018
- [PerCom 2024][12 Mar 2024] UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers. Host: Prof. Christine Julien
- [EfficientML Reading Group][13 Feb 2024] Efficient Continual and On-Device Learning for Edge Computing Platforms. Host: Prof. Olga Saukh
- [SenSys 2023][14 Nov 2023] LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms. Host: Dr. Tarek Abdelzaher
- [SenSys 2023][12 Nov 2023] On-device Training at the Extreme Edge. Host: Dr. Stephen Xia
- [Cambridge Korea Academic Society][25 Mar 2023] Deep Learning at the Extreme Edge. Host: Dr. Gwangbin Bae
- [Korea Military Academy][4 Feb 2022] YONO: All You Need To Represent Multiple Dissimilar Neural Networks on Microcontrollers. Host: Prof. Juhee Kim
- [KAIST][27 Jan 2022] On-device Continual Learning in Mobile Sensing Applications. Host: Prof. Lik-Hang Lee
- [KAIST][27 Jan 2022] You Only Need One Pair of Codebooks to Represent Multiple Deep Learning Models on Extremely Resouce-Constrained Devices. Host: Prof. Junehwa Song
- [University of Cambridge][12 Aug 2021] Efficient Continual Learning in Mobile Sensing Applications. Host: Prof. Nicholas D. Lane
- [University of Cambridge][3 Dec 2019] An Empirical Study of Lifelong Learning on Mobile Applications. Host: Dr. Seyyed Ahmad Javadi
- [Korea Military Academy][8 Oct 2018] Characterization and Prediction of Churning Users in CQAs and LBSNs. Host: Prof. Seonho Lee
- [HKUST][5 Jul 2018] Community effects on Self-Disclosure Behaviors of Users in an Online Social Network. Host: Prof. Pan Hui
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2021
Best Paper Award at SEC 2021 -
2020-2023
Nokia Bell Labs Studentship for PhD Study at the University of Cambridge -
2017-2019
The Postgraduate Studentship for MPhil Study at HKUST -
2014-2016
Samsung Scholarship for Undergraduate Study at SKKU -
2010-2013
National Science and Engineering Undergraduate Scholarship at SKKU -
2016
Honorable Mention at the KIISE conference 2016 -
2015
Honorable Mention for undergraduate papers at the KIISE conference 2015 -
2021
Travel Grant from SEC -
2021
Interspeech Travel Grant from ISCA -
2019
The Research Travel Grant from HKUST -
2016Honored to be a Valedictorian in the college of ICE
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2016Excellent Record Award for Top 3 Graduates in the college of ICE
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2016Outstanding Undergraduate FYP Award in the college of ICE
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2015The Excellence Award in Mobile App Competition
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2013-2016SungKyunKwan University Scholarship for Excellent Records
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2013-2015Dean's List Awards, 4 times at SKKU and once at HKUST
Beer4You
Implemented an Android app which presents information on beers to users when they capture beers' logo using the image recognition. The app further recommends beers to users based on their previous search historiesCompetition, Conn App 2015
[Code | Slides]
Wearable of the future: ABOUT AR
Collaborated with a team of seven members from the various background such as the fashion design, product design, and computer science to develop a future product design in regard to augmented realityInternational Workshop at Samsung Art and Design Institute 2015
[Slides]
Committee
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2023
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2022
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2020
Reviewer
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2023
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2022
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2021
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2020
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2019
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2018
Student Volunteer
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Sep 2019
Extra Activities
Rowing - Won silver medal in HKUST Indoor Rowing Competition in Apr 2015
| photo
Rowing - Won bronze medal in 2015 Hong Kong China Rowing Association Coastal Rowing Championships in Mar 2015
| photo
Marathon - Completed half marathon (21.1km) 2 times in 2013 and 2014 (photo)
Traveling
I love traveling to new places since I can meet entirely new people with different perspectives towards lives, worlds, etc.
You can check countries I have visited here in this web page