Multimodal foundation models for behavioral health and digital medicine

Short Description: Investigate new ML/CV models for analyzing and understanding human nonverbal behavior from video. Specific focus on the design of efficient perceptual algorithms for behavioral cue extraction and novel approaches for modeling people interaction, with application to medical research and practice.

Prerequisite Knowledge: Strong background in machine learning/computer vision/human behavior modeling, with specialization in one or more of the following areas: supervised/unsupervised/self-supervised learning, large vision models, multimodal foundation models, transfer learning, Research experience in one or more of the following areas: multimodal human behavior modeling, affective computing, AI for healthcare, multimodal machine learning.