Current Projects

Easy and Safe Mobile Health Experience

There have been increasing number of mobile health applications available for general population. However, the usability and inproper guidance could result in suboptimal performance, if worse, misdiagnosis. To minimize human error in self-diagnosis using mobile phones, I have been building an smartphone application to guide users to perform the task correctly in real-time using computer vision techniques. I am also exploring a method to ensure sensor inputs (e.g., image, audio, accelerometer) are compatible for the machine learning models to perform at its best performance.

Understanding Relationship between Sleep Tracking App, Sleep, and Job Performance

Sleep is critical to human function, mediating factors like memory, mood, energy, and alertness. Although it is commonly conjectured that a good night’s sleep is important for job performance, this relationship has historically been hard to quantify due to the difficulty of capturing objective measures in real-world contexts. Through an observational study, we tracked participants sleep behaviors, sleep tracking app usage, and their job performance. With this dataset, we are exploring the relationship between sleep and job performance in the wild, and sleep and sleep tracking app. Also, we are exploring the feasiblity of using mobile app interaction time as an indicator of job performance by investigating how mobile app interaction time changes with participant's sleep behavior and circadian rhythms.

Augmenting Ambient Contexts to Various Applications

Context awareness provides better understanding of user, which can be used in many different ways. I've been exploring augmenting ambient acoustic contexts to conversational agents to extend the capability of the existing smart speakers. I've been also working on non-textual communication application that recommends avatars that represent user's current state so that users can simply select and tap to share their states with friends and family.

Publications

Fire in Your Hands: Understanding Thermal Behavior of Smartphones
Soowon Kang, Hyeonwoo Choi, Soo Young Park, Chunjong Park, Jemin Lee, Uichin Lee, and Sung-Ju Lee
ACM Conference on Conference on Mobile Computing and Networking (MobiCom), October, 2019 [pdf]

Zaturi: We Put Together the 25th Hour for You. Create a Book for Your Baby
Bumsoo Kang, Chulhong Min, Wonjung Kim, Inseok Hwang, Chunjong Park, Seungchul Lee, Sung-Ju Lee, and Junehwa Song
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), February, 2017 [pdf]

“Don’t Bother Me. I’m Socializing!”: A Breakpoint-Based Smartphone Notification System
Chunjong Park, Junsung Lim, Juho Kim, Sung-Ju Lee, and Dongman Lee
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), February, 2017 [pdf]

DX: Accurate Latency-based Congestion Feedback for Datacenters
Changhyun Lee, Chunjong Park, Keon Jang, Sue Moon, and Dongsu Han
IEEE/ACM Transaction on Networking, February, 2017 [pdf]

Accurate Latency-based Congestion Feedback for Datacenters
Changhyun Lee, Chunjong Park, Keon Jang, Sue Moon, and Dongsu Han
USENIX Annual Technical Conference (ATC), July, 2015 [pdf]