Sun-Jae Lee
Sungkyunkwan University · Engineering
About the Lab
Professor Sun-Jae Lee's research lab specializes in affective computing, smart home systems, and mobile health, focusing on developing intelligent, context-aware applications using everyday devices like smartphones. The lab explores emotion recognition through embedded sensors, posture monitoring for ergonomic health, and energy-efficient smart home automation using ontology-based reasoning. It also investigates multi-device interaction and the use of real-time transcriptions to enhance remote collaboration in online meetings.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Awareness of the emotion of those who communicate with others is a fundamental challenge in building affective intelligent systems. Emotion is a complex state of the mind influenced by external events, physiological changes, or relationships with others. Because emotions can represent a user's internal context or intention, researchers suggested various methods to measure the user's emotions from analysis of physiological signals, facial expressions, or voice. However, existing methods have prac
We present an ontology-based reasoning approach for saving energy in a smart home setting where a mobile phone can serve as a generic sensor which can collect the inhabitant's contextual data. The paper details an ontology that describes the smart home domain and a prototype to test the system. Finally, we conclude with lessons learned from our work in developing an energy-aware smart home prototype and suggestions for future work.
With the widespread use of smartphones, users tend to use their smartphones for a long period of time with unhealthy postures, bending forward their upper body including the neck. If users keep such an unhealthy posture for a long time, their neck and back muscles get chronically strained, which might cause diseases such as cervical myalgia. To prevent these diseases, we propose a new methodology to monitor the posture of smartphone users with built-in sensors. The proposed mechanism estimates a
The growing trend of multi-device ownerships creates a need and an opportunity to use applications across multiple devices. However, in general, the current app development and usage still remain within the single-device paradigm, falling far short of user expectations. For example, it is currently not possible for a user to dynamically partition an existing live streaming app with chatting capabilities across different devices, such that she watches her favorite broadcast on her smart TV while
Online meetings are indispensable in collaborative remote work environments, but they are vulnerable to distractions due to their distributed and location-agnostic nature. While distraction often leads to a decrease in online meeting quality due to loss of engagement and context, natural multitasking has positive tradeoff effects, such as increased productivity within a given time unit. In this study, we investigate the impact of real-time transcriptions (i.e., full-transcripts, summaries, and k
With the rapid growth of big data, the applications of intellectual property (IP) rights and prior art documents are increasing rapidly. Patent examiners are usually overworked to evaluate inventions referring to a large volume of prior arts in a short period. Such increasing workloads and documents may cause administrative inefficiencies and generate low-quality IPs that hamper technological innovation. Moreover, today's centralized IP administration system is inefficient in processing speed, s
With the widespread use of smartphones, users tend to use their smartphone for a long period of time in unhealthy postures; bending forward the neck and watching the relatively small screen closely with concentration. If users keep such unhealthy postures for a long time, they are susceptible to musculoskeletal disorders and eye problems such as cervical disc and myopia, respectively. To prevent users from having these diseases, we propose a new methodology to monitor the posture of smartphone u
Abstract Instrumentation and control systems significantly affect the safety and reliability of nuclear power plants. In this study, we analyze the cause of failure of the electronic card constituting the instrumentation and control system as it is the most typical reason for the failure of optocouplers. The lifetime of optocouplers must be predicted accurately to ensure high‐reliability nuclear power plants. While acceleration tests have been performed to predict the lifetime of optocouplers mo
The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation. Their superior language understanding and reasoning capabilities allow users to automate complex and repetitive tasks. However, due to the inherent unreliability and high operational cost of LLMs, their practical applicability is quite limited. To address these issues, this paper introduces MobileGPT1, an innovative LLM-based mobile task automator equipped with a human-like app memo
Being able to use a single app across multiple devices can bring novel experiences to the users in various domains including entertainment and productivity. For instance, a user of a video editing app would be able to use a smart pad as a canvas and a smartphone as a remote toolbox so that the toolbox does not occlude the canvas during editing. However, existing approaches do not properly support the single-app multi-device execution due to several limitations, including high development cost, d
Despite the physical advance of an existing single-cell battery system, mobile users are still suffering from low battery anxiety. With a careful analysis of users' battery usage behavior collected for 19,855 hours, we propose a heterogeneous battery system, MixMax, consisting of three complementary battery types tailored to minimizing the low battery time. While composing a heterogeneous battery system opens up a chance to simultaneously improve the capacity and the charging speed, one must fac
Nowadays, people interact with smartphones constantly throughout their daily lives so that smartphones become the most ideal device for recognizing users' physiological and emotional states. In this paper, we present a novel approach for providing users with personalized interface by inferring human emotions based on the touch behavior of a smartphone. Recognizing human emotions is a challenging task and we propose to use touch related data to infer user's emotional states. We also propose a per
Mobile apps offer a variety of features that greatly enhance user experience. However, users still often find it difficult to use mobile apps in the way they want. For example, it is not easy to use multiple apps simultaneously on a small screen of a smartphone. In this paper, we present A-Mash, a mobile platform that aims to simplify the way of interacting with multiple apps concurrently to the level of using a single app only. A key feature of A-Mash is that users can mash up the UIs of differ
Research Areas
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