Director Brain Image Computing Laboratory,
Assistant Professor of Biomedical Engineering,
Case Western Reserve University, Cleveland, OH, USA
Title: Radiomics and Radiogenomics in Neuro-oncology: Opportunities for Precision Medicine
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Biography: Dr. Pallavi Tiwari is an Assistant Professor of Biomedical Engineering and the Director of Brain Image Computing laboratory at Case Western Reserve University. She is also an associate member of the Case Comprehensive Cancer Center. Dr. Tiwari got her PhD from Rutgers University in 2012. In 2016, she founded the Brain Image Computing lab at Case Western Reserve University. Her research interests lie in pattern recognition, data mining, and image analysis for developing automated personalized medicine solutions for neurological disorders including brain tumors. Dr. Tiwari has over 12 years of experience in radiomics and radiogenomics with several publications across brain, lung, breast, and prostate cancers. In 2015, She was named by Government of India as one of 100 women achievers for making a positive impact in the field of Science and Innovation. In 2018, she was selected as one of Crain’s Business Cleveland Forty under 40. Dr. Tiwari has been a recipient of many research related awards including Case-Coulter Translational award, Department of Defense Career Development Award, and Dana Foundation Neuroimaging Award, and is currently leading a team of researchers on multiple projects in prognosis and treatment evaluation in brain tumors.
Associate Professor of Radiology,
University of Pennsylvania, Philadelphia, PA, USA
Title: Clinical Perspective of Computational Neuro-Oncology
Biography: Dr. Michel Bilello is an associate professor in the department of Radiology, division of Neuroradiology, at the University of Pennsylvania. Dr. Bilello has a dual medical/engineering background. He is actively pursuing neuroimaging research, applying image processing techniques to solving clinical questions, particularly in multiple sclerosis, neurodegenerative disorders, cerebrovascular disease, and primary brain neoplasms. His research involves looking for image-based biomarkers to quantify disease and predict progression. He has developed a computer-aided detection (CAD) software to detect new lesions on brain MRI in patients with multiple sclerosis (MS). This program has been fully integrated into the clinical workflow and is being used multiple times daily by all neuroradiologists in the department.
Professor of Computer Science and Medicine,
TU München, Germany
Title: The BRATS challenge: how accurate are algorithms?
Biography: Dr. Menze is working in the field of medical image computing. He develops algorithms that analyze biomedical images using functional and probabilistic models from machine learning, computer vision, and biophysics. The emphasis of this work is on applications in clinical neuroimaging and the personalized modeling of tumor growth. He has organized workshops on medical computer vision and on neuroimaging at MICCAI, NIPS and CVPR, served as a member of the program committee of MICCAI and is a member of the editorial board of the Medical Image Analysis journal.
Professor Menze studied physics in Heidelberg (Germany) and Uppsala (Sweden) and obtained a PhD in computer science from Heidelberg University in 2007. He subsequently moved to Boston (USA) where he worked as a postdoctoral researcher at Harvard University, Harvard Medical School, and MIT. This was followed by senior research position at Inria in Sophia-Antipolis (France) and at ETH Zurich (Switzerland). In 2013 he was the first scholar to have been appointed a Rudolf Moessbauer Professor at TUM. In 2019 he was visiting professor at Maastricht University. At TUM he heads the "Image-based Biomedical Modeling Group" at the Munich School of Bioengineering and the Center for Translational Cancer Research.
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