Dr. Nils Daniel Forkert, PhD
Cumming School of Medicine, Department of Radiology
Cumming School of Medicine, Department of Clinical Neurosciences
Schulich School of Engineering, Department of Electrical and Software Engineering
Child Health Data Science Program Director
Alberta Children's Hospital Research Institute
One Child Every Child Comprehensive Data Member
University of Calgary
Hotchkiss Brain Institute
Postdoctoral Felllowship Medical Image Processing, Stanford University,
Doctorate Medical Image Processing, University of Hamburg,
MSc Medical Physics, Technical University of Kaiserslautern,
Dipl.-Inf. (German Diploma) Computer Science, University of Hamburg,
Dr. Nils Daniel Forkert is a Full Professor at the University of Calgary in the Departments of Radiology, Clinical Neurosciences, and Electrical and Software Engineering. He received his German diploma in Computer Science from the University of Hamburg, his master’s degree in medical physics from the Technical University of Kaiserslautern, his PhD in computer science 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 pre-clinical 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 160 peer-reviewed manuscripts, over 75 full-length proceedings papers, over 150 conference abstracts, 1 book, and 1 book chapter. He has received major funding from the Canadian Institutes of Health Research (CIHR), 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 three postdoctoral fellows, seven PhD students, and six MSc students demonstrating his dedication to training the next generation of data science researchers.
Areas of Research
The focus of my research is to develop and evaluate new image processing methods, algorithms, and software tools for the analysis of medical images. This includes the image-based extraction of clinically relevant parameters and biomarkers describing the morphology and function of organs. In doing so, we aim to support clinical studies and preclinical research as well as developing and improving computer-aided diagnosis and patient-specific prediction models with a special focus on, but not limited to, the human brain. Additionally, we are developing advanced machine learning models for various diseases using multi-modal data sources, not limited to image-based features.
- Canada Research Chair in Medical Image Analysis, 2020
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