Mark Schurgin, PhD, is a research lead at Google Health. He brings 14+ years of experience conducting human-centered research in academic, clinical and industry settings. Mark has been recognized with the Early Career Award by the American Psychological Association (APA), and by John Hopkins University with the G. Stanley Hall Scholar’s Award for outstanding dissertation. He has also authored several recognized papers (e.g., papers receiving editor's choice designation, best paper). He received his PhD in Psychological & Brain Sciences from Johns Hopkins University in 2017.
Below is a selection of potential talks. Please contact Mark for additional talk topics.
How to leverage the Brain to inform UX Design
How does the brain process visual information? Why do we attend to some things or get distracted by other things? What makes something we see memorable? Mark illustrates through dazzling illusions the fundamental principles for how humans perceive and remember the world around us. But more than just a magic trick, Mark will show you how an understanding of UX design principles powered by your newfound knowledge of the human visual system can improve how you develop interactions with your users.
Conducting UX Research in Sensitive Settings
In a space with heightened sensitivity (healthcare), careful considerations around privacy, ethics, and legal are necessary to conduct research. While Google has a UX research infrastructure team that supports the company world-wide across all products, Google Health needed additional, specialized infrastructure to consider specific laws, regulations, and industry standards. Mark discusses how he helped establish the processes that unlocked Google Health researchers to work in symphony with privacy, ethics, and legal considerations to ensure the highest standards that the user always comes first.
Rethinking Visual Memory
Dominant models of visual memory have made strong arguments that there are fixed limits on working memory capacity and there is a strong distinction between working memory and long-term memory representations. Mark demonstrates that once perception is taken into account aspects of memory that have required fundamentally different models -- across different stimuli, tasks, and even the distinction between working and long-term memory -- can be explained with a unitary signal detection framework. These results lead to a substantial reinterpretation of the relationship between perception, working memory and long-term memory.
CHI Conference on Human Factors in Computing Systems. Yokohama, Japan (2021).
Washington University in St. Louis. St Louis, MO (2020).
Arizona State University (ASU). Tempe, AZ (2020).
UX Insight, Breda, Netherlands (2020).
UX University (Google). Sunnyvale, CA (2019).
Harvard University. Cambridge MA (2018).
Massachusetts Institute of Technology (MIT). Cambridge MA (2018).
University of San Diego. San Diego, CA (2018).
University of California, San Diego (UCSD). San Diego, CA (2018).
University of California, Santa Cruz (UCSC). Santa Cruz, CA (2018).
Society for Neuroscience. San Diego, CA (2018).
Vision Sciences Society. St. Pete Beach, FL (2018).