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Chulhong Min - IEEE Xplore Author Profile
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Chulhong Min

Publications
15
Citations
176
Publications by Year
20112025
Co-Authors:
Show All Co-Authors (24)
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Chulhong Min

Affiliation

Nokia Bell Labs, Cambridge, U.K.

Publication Topics

Biography

Chulhong Min is a research scientist at Nokia Bell Labs, Cambridge, U.K. His research interests include mobile and wearable systems, and the Internet of Things. He received the Ph.D. degree in computer science from KAIST in 2016. Contact him at chulhong.min@nokia-bell-labs.com.(Based on document published on 12 August 2019).
Publications
15
Citations
176
Publications by Year
20112025
Co-Authors:
Show All Co-Authors (24)
Author's Published Works

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Argus: Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Cameras

Juheon Yi;Utku Günay Acer;Fahim Kawsar;Chulhong Min

IEEE Transactions on Mobile Computing
Year: 2025 | Volume: 24, Issue: 1 | Journal Article |
Overlapping cameras offer exciting opportunities to view a scene from different angles, allowing for more advanced, comprehensive and robust analysis. However, existing video analytics systems for multi-camera streams are mostly limited to (i) per-camera processing and aggregation and (ii) workload-agnostic centralized processing architectures. In this paper, we present Argus, a distributed video ...Show More

Argus: Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Cameras

Juheon Yi;Utku Günay Acer;Fahim Kawsar;Chulhong Min

Year: 2025 | Volume: 24, Issue: 1 | Journal Article |

Emerging Paradigms in Wearable Security: Adaptable and Secure Sandboxing for On-the-Fly Collaboration Among Wearables

Diana A. Vasile;Fahim Kawsar;Chulhong Min

IEEE Security & Privacy
Year: 2024 | Volume: 22, Issue: 6 | Magazine Article |
We propose a novel security protocol for on-the-fly collaboration among wearables, addressing significant security challenges, such as data exposure and false information injection. Leveraging wearables’ position on the body, our protocol ensures secure collaboration and enables new possibilities for ubiquitous computing.Show More

Emerging Paradigms in Wearable Security: Adaptable and Secure Sandboxing for On-the-Fly Collaboration Among Wearables

Diana A. Vasile;Fahim Kawsar;Chulhong Min

Year: 2024 | Volume: 22, Issue: 6 | Magazine Article |

SensiX: A System for Best-Effort Inference of Machine Learning Models in Multi-Device Environments

Chulhong Min;Akhil Mathur;Alessandro Montanari;Fahim Kawsar

IEEE Transactions on Mobile Computing
Year: 2023 | Volume: 22, Issue: 9 | Journal Article |
Cited by: Papers (2)
Multiple sensory devices on and around us are on the rise and require us to redesign a system to make an inference of ML models accurate, robust, and efficient at the deployment time. While this multiplicity opens up an exciting opportunity to leverage sensor redundancy and high availability, it is still extremely challenging to benefit from such multiplicity and boost the runtime performance of d...Show More

SensiX: A System for Best-Effort Inference of Machine Learning Models in Multi-Device Environments

Chulhong Min;Akhil Mathur;Alessandro Montanari;Fahim Kawsar

Year: 2023 | Volume: 22, Issue: 9 | Journal Article |

SleepGAN: Towards Personalized Sleep Therapy Music

Jing Yang;Chulhong Min;Akhil Mathur;Fahim Kawsar

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
Sleep deficiency and disorders are one of the most unsolved public health challenges of modern times. Music therapy is a promising approach, offering a cheap and non-invasive solution to improve sleep quality. However, the choice of therapeutic sleep music is highly limited for users because such music needs to be specially chosen and made by sleep therapists. It could potentially lead to the inef...Show More

SleepGAN: Towards Personalized Sleep Therapy Music

Jing Yang;Chulhong Min;Akhil Mathur;Fahim Kawsar

Year: 2022 | Conference Paper |

In-Ear PPG for Vital Signs

Andrea Ferlini;Alessandro Montanari;Chulhong Min;Hongwei Li;Ugo Sassi;Fahim Kawsar

IEEE Pervasive Computing
Year: 2022 | Volume: 21, Issue: 1 | Magazine Article |
Cited by: Papers (18)
Earables are now pervasive, and their established purpose, ergonomy, and noninvasive interaction uncover exciting opportunities for sensing and healthcare research. However, it is critical to understand and characterize sensory measurements’ accuracy in earables impacting healthcare decisions. We report a systematic characterization of in-ear photoplethysmography (PPG) in measuring vital signs: he...Show More

In-Ear PPG for Vital Signs

Andrea Ferlini;Alessandro Montanari;Chulhong Min;Hongwei Li;Ugo Sassi;Fahim Kawsar

Year: 2022 | Volume: 21, Issue: 1 | Magazine Article |

Deploying Collaborative Machine Learning Systems in Edge with Multiple Cameras

Si Young Jang;Utku Günay Acer;Chulhong Min;Fahim Kawsar

2021 Thirteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Advancement in hardware capability has opened up the possibility of performing ML inference tasks at the edge using a large volume of sensory data generated from IoT devices such as cameras. As cameras become more pervasive, edge systems need to process streams from multiple sources with overlapping fields-of-view. In this position paper, we describe a collaborative sensing mechanism at the edge f...Show More

Deploying Collaborative Machine Learning Systems in Edge with Multiple Cameras

Si Young Jang;Utku Günay Acer;Chulhong Min;Fahim Kawsar

Year: 2021 | Conference Paper |

Scalable Power Impact Prediction of Mobile Sensing Applications at Pre-Installation Time

Chulhong Min;Youngki Lee;Chungkuk Yoo;Inseok Hwang;Younghyun Ju;Junehwa Song;Seungwoo Kang

IEEE Transactions on Mobile Computing
Year: 2020 | Volume: 19, Issue: 6 | Journal Article |
Cited by: Papers (1)
Today's smartphone application (hereinafter `app') markets do not provide information on power consumption of apps, which is essential for users. Continuous sensing apps make this problem more severe because significant power is consumed without the users' awareness. We propose PowerForecaster to break through such an exhaustive cycle. It provides users with personalized estimation of sensing apps...Show More

Scalable Power Impact Prediction of Mobile Sensing Applications at Pre-Installation Time

Chulhong Min;Youngki Lee;Chungkuk Yoo;Inseok Hwang;Younghyun Ju;Junehwa Song;Seungwoo Kang

Year: 2020 | Volume: 19, Issue: 6 | Journal Article |

Towards Interpersonal Assistants: Next-Generation Conversational Agents

Inseok Hwang;Youngki Lee;Chungkuk Yoo;Chulhong Min;Dongsun Yim;John Kim

IEEE Pervasive Computing
Year: 2019 | Volume: 18, Issue: 2 | Magazine Article |
Cited by: Papers (14)
We propose novel interpersonal assistants, a next-generation conversational agent which is always-on, unobtrusively serving natural human-to-human conversations. We deepen the motivation and design insights with real practices in language delays and parent–child conflicts. We then present a common platform initiative to effectively support rapid development of interpersonal assistant applications,...Show More

Towards Interpersonal Assistants: Next-Generation Conversational Agents

Inseok Hwang;Youngki Lee;Chungkuk Yoo;Chulhong Min;Dongsun Yim;John Kim

Year: 2019 | Volume: 18, Issue: 2 | Magazine Article |

On Tracking the Physicality of Wi-Fi: A Subspace Approach

Mohammed Alloulah;Anton Isopoussu;Chulhong Min;Fahim Kawsar

IEEE Access
Year: 2019 | Volume: 7 | Journal Article |
Cited by: Papers (4)
Wi-Fi channel state information (CSI) has emerged as a plausible modality for sensing different human activities as a function of modulations in the wireless signal that travels between wireless devices. Until now, most research has taken a statistical approach and/or purpose-built inference pipeline. Although interesting, these approaches struggle to sustain sensing performances beyond experiment...Show More

On Tracking the Physicality of Wi-Fi: A Subspace Approach

Mohammed Alloulah;Anton Isopoussu;Chulhong Min;Fahim Kawsar

Year: 2019 | Volume: 7 | Journal Article |

Earables for Personal-Scale Behavior Analytics

Fahim Kawsar;Chulhong Min;Akhil Mathur;Alessandro Montanari

IEEE Pervasive Computing
Year: 2018 | Volume: 17, Issue: 3 | Magazine Article |
Cited by: Papers (98)
The rise of consumer wearables promises to have a profound impact on peoples lives by going beyond counting steps. Wearables such as eSense-an in-ear multisensory stereo device-for personal-scale behavior analytics could help accelerate our understanding of a wide range of human activities in a nonintrusive manner.Show More

Earables for Personal-Scale Behavior Analytics

Fahim Kawsar;Chulhong Min;Akhil Mathur;Alessandro Montanari

Year: 2018 | Volume: 17, Issue: 3 | Magazine Article |

CoMon+: A Cooperative Context Monitoring System for Multi-Device Personal Sensing Environments

Youngki Lee;Seungwoo Kang;Chulhong Min;Younghyun Ju;Inseok Hwang;Junehwa Song

IEEE Transactions on Mobile Computing
Year: 2016 | Volume: 15, Issue: 8 | Journal Article |
Cited by: Papers (9)
Continuous mobile sensing applications are emerging. Despite their usefulness, their real-world adoption has been slow. Many users are turned away by the drastic battery drain caused by continuous sensing and processing. In this paper, we propose CoMon+, a novel cooperative context monitoring system, which addresses the energy problem through opportunistic cooperation among nearby users. For effec...Show More

CoMon+: A Cooperative Context Monitoring System for Multi-Device Personal Sensing Environments

Youngki Lee;Seungwoo Kang;Chulhong Min;Younghyun Ju;Inseok Hwang;Junehwa Song

Year: 2016 | Volume: 15, Issue: 8 | Journal Article |

An Active Resource Orchestration Framework for PAN-Scale, Sensor-Rich Environments

Youngki Lee;Chulhong Min;Younghyun Ju;Seungwoo Kang;Yunseok Rhee;Junehwa Song

IEEE Transactions on Mobile Computing
Year: 2014 | Volume: 13, Issue: 3 | Journal Article |
Cited by: Papers (11)
In this paper, we present Orchestrator, an active resource orchestration framework for a PAN-scale sensor-rich mobile computing platform. Incorporating diverse sensing devices connected to a mobile phone, the platform will serve as a common base to accommodate personal context-aware applications. A major challenge for the platform is to simultaneously support concurrent applications requiring cont...Show More

An Active Resource Orchestration Framework for PAN-Scale, Sensor-Rich Environments

Youngki Lee;Chulhong Min;Younghyun Ju;Seungwoo Kang;Yunseok Rhee;Junehwa Song

Year: 2014 | Volume: 13, Issue: 3 | Journal Article |

MobiCon: Mobile context monitoring platform: Incorporating context-awareness to smartphone-centric personal sensor networks

Youngki Lee;Younghyun Ju;Chulhong Min;Jihyun Yu;Junehwa Song

2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)
Year: 2012 | Conference Paper |
Cited by: Papers (8) | Patents (2)
In this demonstration, we will show MobiCon, a context monitoring platform; it runs over smartphones and sensor OSs, and facilitates development and deployment of everyday context-aware applications. For many years, lots of research efforts have been made in building low-cost, yet effective sensor networks for various application domains such as structural health monitoring of bridges, disaster re...Show More

MobiCon: Mobile context monitoring platform: Incorporating context-awareness to smartphone-centric personal sensor networks

Youngki Lee;Younghyun Ju;Chulhong Min;Jihyun Yu;Junehwa Song

Year: 2012 | Conference Paper |

An efficient dataflow execution method for mobile context monitoring applications

Younghyun Ju;Chulhong Min;Youngki Lee;Jihyun Yu;Junehwa Song

2012 IEEE International Conference on Pervasive Computing and Communications
Year: 2012 | Conference Paper |
Cited by: Papers (6) | Patents (1)
In this paper, we propose a novel efficient dataflow execution method for mobile context monitoring applications. As a key approach to minimize the execution overhead, we propose a new dataflow execution model, producer-oriented model. Compared to the conventional consumer-oriented model adopted in stream processing engines, our model significantly reduces execution overhead to process context mon...Show More

An efficient dataflow execution method for mobile context monitoring applications

Younghyun Ju;Chulhong Min;Youngki Lee;Jihyun Yu;Junehwa Song

Year: 2012 | Conference Paper |

A mobile context monitoring platform for pervasive computing environments

Youngki Lee;Chulhong Min;Younghyun Ju;Saumay Pushp;Junehwa Song

5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)
Year: 2011 | Conference Paper |
In this paper, we present a new mobile platform to support emerging pervasive applications in a Personal Area Network (PAN)-scale dynamic mobile computing environment. The PAN-scale computing environment will constitute an important part of future pervasive-space technology with highly proactive applications, requiring continuous monitoring of users' contexts. The context-aware applications impose...Show More

A mobile context monitoring platform for pervasive computing environments

Youngki Lee;Chulhong Min;Younghyun Ju;Saumay Pushp;Junehwa Song

Year: 2011 | Conference Paper |

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