2026 Exploratory CRT Awards
Machine learning-driven roadblocks detection through videogame-powered building collapse simulation
PI: Daniele Malomo (Assistant Professor, Civil Engineering)
This project will fuse real-time physics engines from the videogame world with machine learning and transportation network analysis to anticipate where collapsed buildings will block streets during disasters, and how this will affect emergency access and evacuation.
Gender, Choice, and Trust in AI-Mediated Mental Health Care
PI: Skyler Wang (Assistant Professor, Sociology)
Co-PI: Claire Boone (Assistant Professor, Economics)
As chatbots become more prevalent in mental health care, whether as supplements or substitutes for human therapists, it is crucial to understand how users perceive chatbot gender and how this perception shapes their experience. In this project, we ask: How does “gendering” AI mental health tools help and for whom?
2026 Proof-of-Concept CRT Awards
Understanding human choice behaviour by leveraging massive realworld supermarket transaction datasets
PI: Ross Otto (Associate Professor, Psychology)
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.
VibratoAI: Artificial Intelligence–Assisted Vibrato Analysis for Vocal Health Monitoring and Early Disease Diagnosis
PI: Yaoyao Fiona Zhao (Associate Professor, Mechanical Engineering)
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).
