Extensive information in our daily life continually competes with human cognitive resources (e.g., attention and workload). It requires us to decide which information is essential and which should be filtered. A growing body of research has indicated that information overload has caused difficulties in understanding issues, making decisions, and likely leading us to ignore important messages. Simultaneously, such extensive information could contain collective intelligence contributed by thousands of users, which is a valuable resource to understand users' perceptions and behaviors at a massive scale.

In this talk, I will present a series of works in two research threads that 1) addressed cognitive resource allocation using brain-sensing techniques, and 2) utilized the collective knowledge scattered within massive information using visualization and machine learning from a human-centered perspective. The first thread results generated neural-based design implications to precisely designate users' mental resources tailored to contexts. For the second thread, I will introduce the crowdsourcing projects that I built visualization interfaces using large-scale data to shape users' behavior and reveal design insights. Finally, I will share the directions for my future research extending from these studies.

Dr. Fu-Yin Cherng is a postdoctoral researcher who works with Prof. Hao-Chuan Wang in the Department of Computer Science at UC Davis. She received a Ph.D. degree from the Department of Computer Science at National Chiao Tung University (NCTU), Taiwan, in 2019, advised by Prof. Wen-Chieh Lin. From 2016 to 2017, Fu-Yin was a doctoral research assistant for Prof. Pierre Dillenbourg at EPFLin Switzerland. Fu-Yin's general research interest is Human-computer Interaction, focusing on understanding users' cognitive processes with physiological indicators. She has also worked on derived design implications using data science techniques and crowdsourcing. Fu-Yin has published several papers, including two papers with CHI best paper honorable mention award within five years at top-tier conferences and journals with over a hundred citations. As an active researcher, she served as a committee member in MobileHCI'19 and TAICHI'20, and reviewer for ACM CHI, CSCW, IEEE VR, etc.