Ross Otto (Associate Professor, Psychology)
Understanding human choice behaviour by leveraging massive realworld supermarket transaction datasets
This project will carry out a set of novel analyses of a massive consumer choice dataset in order to 1) elucidate human decision-making phenomena which are well-documented in small scale, artificial (i.e. laboratory) settings but in many cases are not well understood in real-world settings and 2) understand how rich, multi-dimensional individual differences in consumers and purchase histories bear upon choice processes and predict choice behavior.
Yaoyao Fiona Zhao (Associate Professor, Mechanical Engineering)
VibratoAI: Artificial Intelligence–Assisted Vibrato Analysis for Vocal Health Monitoring and Early Disease Diagnosis
This project focuses on a transformative research direction that uses machine learning, digital acoustics, and vocal physiology to determine whether vibrato variability — the natural modulation in pitch and amplitude during sustained phonation — can serve as a non-invasive digital biomarker for early detection of voice disorders such as muscle tension dysphonia (MTD) and temporomandibular disorders (TMD).
