Sho Tsuji is an Assistant Professor at the University of Tokyo. She studies the role of social cues, specifically interactivity, on infant word learning. Using techniques like gaze-contingent eye-tracking, she tries to disentangle the influence of social cues from the presence of a human interaction partner during learning.

During her PhD, Sho conducted her first meta-analysis on infant vowel discrimination and since then, she has been convinced that a meta-analysis is a great starting point for many scientific projects. Based on the infrastructure she built around her and other meta-analyses, her team proposed the concept of community-augmented meta-analyses (Tsuji, Bergmann, & Cristia, 2014), a concept that later lead to MetaLab, a project funded by a SSMART grant. MetaLab is an open-access, dynamic, and growing database of meta-analyses on infant language development, and aims to lower the hurdles of using meta-analytic tools by providing educational material as well as ready-to-use visualization and calculation tools. She was also a postdoctoral researcher at University of Pennsylvania and Laboratoire de Sciences Cognitives et Psycholinguistique.

Dr. Tsuiji promotes the use and creation of meta-analysis by teaching the technique during workshops, classes, and conferences, as well as continuing to develop the educational material for MetaLab (like this video tutorial series).