Youngki Lee is an assistant professor in the Computer Science and Engineering Department of Seoul National University. He received his PhD from the computer science department in KAIST, Korea, and worked at Singapore Management University from 2013 to 2018. Youngki has broad research interests in building experimental and creative software systems, which involve multi-dimensional considerations across operating systems, applications, and users. More specifically, he has been developing mobile and sensor systems to enable always-available and highly enriched awareness of human behavior, emotion, and surrounding contexts. Also, he addressed core technical challenges such as improving energy efficiency, handling concurrency, and improving recognition accuracy. Furthermore, he has been building and deploying innovative mobile sensing applications in various application domains such as daily healthcare, childcare, education in collaboration with domain experts. He published a stream of his work in top-tier conferences and journals such as ACM MobiSys, ACM SenSys, ACM UbiComp, IEEE TMC. He served a program co-chair for UbiComp 2018 and technical program and organizing committees for many top-tier conferences. More details are available at http://youngkilee.blogspot.com.
강연요약 :
The continuous advance in mobile and AI technology is opening up an unprecedented opportunity to innovate conventional practices in education, elderly care, transportation, automated homes, and many other application domains. Plenty of consumer devices such as smartphones, IoT devices, wearables continuously collect a massive volume of personal data (e.g., conversation, video, activities, app use, physiological data). The data are transformed and abstracted into useful insights and knowledge using various AI algorithms, from which valuable applications can be designed. In this talk, I will (1) introduce various examples of emerging AI-driven mobile apps in a few application domains, (1) technology trend of innovating networked mobile systems to enable such AI-based mobile apps, and (3) potential challenges and opportunities in designing such systems and applications.
