Technical - Partner Event
AI Seminar - Nils Forkert
When
Jan. 29, 2021 - Jan. 29, 2021
12:00 PM - 1:00 PM (MST)
Where
Online
Online
Abstract: In this talk, I will present selected applications of machine learning methods for medical image analysis for computer-aided diagnosis support and clinical research, which includes the use of conventional machine learning techniques as well as novel deep learning methods with a primary application to cerebrovascular and neurological diseases. Furthermore, novel research projects related to patient privacy protection and explainable artificial intelligence will be presented.
Presenter Bio: Dr. Nils Daniel Forkert is an Associate Professor at the University of Calgary in the Departments of Radiology and Clinical Neurosciences. He received his German diploma in computer science in 2009 from the University of Hamburg, his master’s degree in medical physics in 2012 from the Technical University of Kaiserslautern, his PhD in computer science in 2013 from the University of Hamburg, and completed a postdoctoral fellowship at Stanford University before joining the University of Calgary as an Assistant Professor in 2014. He is an imaging and machine learning scientist who develops new image processing methods, predictive algorithms, and software tools for the analysis of medical data. This includes the extraction of clinically relevant parameters and biomarkers from medical data describing the morphology and function of organs with the aim of supporting clinical studies and preclinical research as well as developing computer-aided diagnosis and patient-specific, precision-medicine, prediction models using machine learning based on multi-modal medical data. Dr. Forkert is a Canada Research Chair (Tier 2) in Medical Image Analysis, and Director of the Child Health Data Science Program of the Alberta Children's Hospital Research Institute as well as the Theme Lead for Machine Learning in Neuroscience of the Hotchkiss Brain Institute at the University of Calgary. He has published over 120 peer-reviewed manuscripts, over 50 full-length proceedings papers, over 130 conference abstracts, and 1 book. He has received major funding from the Natural Sciences and Engineering Research Council, the Heart and Stroke Foundation, Calgary Foundation, and the National Institutes of Health as a PI or co-PI. He currently supervises four postdoctoral fellows, six PhD students, and five MSc students demonstrating his dedication to training the next generation of data science researchers.
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