Speaker

Yincheng Jin, University at Buffalo

Abstract

Despite the ever-growing advances in smart devices (e.g., earbuds, smart speakers, smartphones, smartwatches) and artificial intelligence around us, our lives are still far from truly intelligent. To further build an intelligent environment to promote the quality of life, my research lies in the intersection between human sensing and applied machine learning, especially addressing the increasing demands for human-computer interactions (HCI), healthcare, and affective computing. Specifically, my research efforts have primarily focused on the following three themes: 1) Effective Communications: exploring effective communication solutions by deploying deep learning models on various smart mobile computing platforms; 2) Affective Computing: detecting facial expressions to investigate human emotional and engagement status; 3) Smart Health: investigating novel methods for early ear disease diagnosis. My works have been published in top-tier computer science venues, including Ubicomp, MobiSys, and IUI, and some research results have been widely reported in various high-impact media outlets.

Biography

Yincheng Jin is a 5th-year Ph.D. candidate in the CSE department from University at Buffalo, advised by Professor Zhanpeng Jin. His research focuses on mobile computing, Internet-of-Things, cyber-physical systems, applied machine learning, and smart health. Yincheng's work has been published in top conferences such as UbiComp, MobiSys, and IUI. Additionally, his work has been highlighted by several popular media outlets, including New Scientist, UB News, New Atlas.