Rate My Professor Bo Cao

Bo Cao is an Associate Professor in the Department of Psychiatry within the Faculty of Medicine & Dentistry at the University of Alberta, holding the Canada Research Chair (Tier 2) in Computational Psychiatry. He possesses a BSc in mathematics, an MSc in psychology, a PhD in computational neuroscience, and postdoctoral training in neuroimaging and psychiatry. As co-director of the Computational Psychiatry research group, Cao directs a multidisciplinary team that applies advanced machine learning, data science, and data mining techniques to enhance psychiatric diagnosis, prognosis, and personalized treatment. His research specializes in computational psychiatry and precision medicine for mental health, utilizing multimodal data such as electronic health records, brain imaging, genetics, biological markers, behavioral assessments, cognitive tests, and clinical measurements to identify objective biomarkers for disorders including schizophrenia, bipolar disorder, major depressive disorder, ADHD, opioid use disorder, and anxiety. Additional interests encompass brain development and aging across the lifespan, examining how lifestyle, environmental, social, cognitive, and genetic factors influence mental and physical health interactions during aging, as well as neuromodulation and neurofeedback applications.

Cao's contributions have garnered over 6,459 citations on Google Scholar, underscoring his impact in the field. Notable publications include 'Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group' (Molecular Psychiatry, 2017), 'Treatment response prediction and individualized identification of first-episode drug-naïve schizophrenia using brain functional connectivity' (Molecular Psychiatry, 2020), 'Hippocampal subfield volumes in mood disorders' (Molecular Psychiatry, 2017), 'The impact of machine learning techniques in the study of bipolar disorder: a systematic review' (Neuroscience & Biobehavioral Reviews, 2017), and 'Lifespan gyrification trajectories of human brain in healthy individuals and patients with major psychiatric disorders' (Scientific Reports, 2017). Recent works feature prospective predictions of anxiety onset using the Canadian Longitudinal Study on Aging (Journal of Affective Disorders, 2024), machine learning for opioid overdose risk, ADHD screening in kindergarten students, and quality of life improvements in depression treatment. His efforts extend to collaborations with institutions like IBM Centers for Advanced Studies Alberta and membership in AI4Society, the Neuroscience and Mental Health Institute, and the Women and Children's Health Research Institute.