Danilo Bzdok (hosted by CIS) – “Population neuroscience meets computer-age statistics: Extending what we can learn about the brain?”
“Population neuroscience meets computer-age statistics: Extending what we can learn about the brain?”
Abstract: Biomedical datasets are rapidly growing in information granularity, sample size, and the complexity of meta-information. These emerging opportunities open always more biological and medical fields to data-led research programs that leverage advanced machine-learning techniques.
In several examples in the area of population brain-imaging, I will explore and discuss how long-standing neuroscience questions can be revisited, reformulated as a pattern-learning problem, and new insights be translated back into the application domain.
Special attention will be devoted to i) how discovery of salient structure in high-dimensional data may be directly integrated with achieving accurate predictions at the single-subject level, ii) how such individualized predictions may be complementary to statistically significant group difference foundational for evidence-based medicine, and iii) how recent extensions of classical analysis methods can jointly appreciate data from different levels of observation.
Machine learning is a core technology that offers new strategies for generating knowledge from current and future large-scale datasets to extent our understanding of and enable rigorous data-guided decisions about human biology and disease trajectories.
Bio: Danilo Bzdok has studied medicine between 2006 and 2012 at RWTH Aachen University, Université de Lausanne, and Harvard Medical School. From 2013 to 2015 he then pursued a PhD in computer science on machine learning working at INRIA Saclay & Neurospin near Paris and Heinrich-Heine University Düsseldorf. From 2015 to 2019 Dr. Bzdok headed the section for “Social and Affective Neuroscience” at the Department of Psychiatry, RWTH Aachen University, as an Assistant Professor. Since 2019, he is Associate Professor and Canada CIFAR Chair in AI at the Montreal Neurological Institute (MNI) at McGill University as well as Appointed Faculty at Mila Quebec AI Institute, Montreal, Canada.