Keynotes

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Prof. Christos Davatzikos

Christos Davatzikos is the Wallace T. Miller Sr. Professor of Radiology at the University of Pennsylvania, and Director of the Center for Biomedical Image Computing and Analytics. He holds a secondary appointment in Electrical and Systems Engineering at Penn as well as at the Bioengineering an Applied Mathematics graduate groups. He obtained his undergraduate degree by the National Technical University of Athens, Greece in 1989, and his Ph.D. degree from Johns Hopkins, in 1994, on a Fulbright scholarship. He then joined the faculty in Radiology and later in Computer Science, where he founded and directed the Neuroimaging Laboratory. In 2002 he moved to Penn, where he founded and directed the section of biomedical image analysis. Dr. Davatzikos’ interests are in medical image analysis. He oversees a diverse research program ranging from basic problems of imaging pattern analysis and machine learning to a variety of clinical studies of aging and Alzheimer’s Disease, schizophrenia, brain cancer, and brain development. Dr. Davatzikos has served on a variety of scientific journal editorial boards and grant review committees. He is an IEEE fellow and a fellow of the American Institute for Medical and Biological Engineering.


 

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Dr. Gaël Varoquaux

Gaël Varoquaux is a tenured computer-science researcher at INRIA. His research develops statistical learning tools for functional neuroimaging data with application to mapping brain of cognition and pathologies. In addition, he is heavily invested in software development for data science, as project-lead for scikit-learn, one of the reference machine-learning toolboxes, and on joblib, Mayavi, and nilearn. Varoquaux has contributed key methods for functional brain atlasing, extracting brain connectomes, population studies, as well as efficient models for high-dimensional data-scarce machine learning beyond brain imaging. He has a Ph.D. in quantum physics and is a graduate of Ecole Normale Superieure, Paris.


 

Jian Kang

Dr. Jian Kang

Jian Kang is an Associate Professor in the Department of Biostatistics at the University of Michigan, Ann Arbor.  He received his Ph.D. in Biostatistics from the University of Michigan in 2011. He was an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Radiology and Imaging Sciences at Emory University from 2011 – 2015. He was a core faculty member in the Center for Biomedical Imaging Statistics (CBIS) at Emory University.  His primary research interests are in Bayesian machine learning methods for large-scale complex biomedical data with application in biomedical imaging, precision medicine, and genetics.