Where and What to Look: Learning to Understand the Visual World in Autistic Brains

Tuesday, September 3, 2019 - 1:25pm - 2:25pm
Lind 305
Catherine Zhao (University of Minnesota, Twin Cities)
Machine learning has gained increasing attention and started to impact healthcare. In this talk, I will discuss the challenges and our work on using machine learning methods in mental health. I will discuss recent innovations on data, experiments, and models. As an example, I will talk about visual behaviors and elaborate findings that decipher the neurobehavioral signature of autism. I will then demonstrate deep learning models that are able to learn semantic attributes from complex natural scenes, leading to breakthrough performance in behavior prediction and identifying people with autism. I will discuss these technological innovations in the context of clinical applications.

Catherine Qi Zhao is an assistant professor in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities. Her main research interests include computer vision, machine learning, cognitive neuroscience, and mental disorders. Dr. Zhao has published about 50 journal and conference papers in top-tier venues including Neuron, Current Biology, Nature Communications, TPAMI, IJCV, CVPR, ICCV, ECCV, NIPS and ICML, and edited a book with Springer, titled Computational and Cognitive Neuroscience of Vision, that provides a systematic and comprehensive overview of vision from various perspectives, ranging from neuroscience to cognition, and from computational principles to engineering developments.