Le Lu received an MSE in 2004 and a PhD in 2007 in Computer Science from Johns Hopkins University. Prior to and during his PhD, he completed two year-long internships at Microsoft Research. In 2006, he joined Siemens Corporate Research at Princeton, New Jersey as a research scientist. He eventually served both as a member of the Medical Solutions’ computer-aided diagnosis & Therapy group and as a senior staff scientist, until 2013. During his seven years at Siemens, he made significant contributions to the company’s CT colonography and Lung CAD product lines. From 2013 to 2017, Dr. Lu served as a staff scientist in the Radiology and Imaging Sciences department of the National Institutes of Health Clinical Center. He then went on to found Nvidia’s medical image analysis group, in which he held the position of senior research manager until June 2018. Since then, he has been the Executive Director at PAII Inc., Bethesda Research lab, Maryland, USA. Dr. Lu's research interests lie in medical image computing/analysis, statistical/deep learning, clinical informatics and novel imaging biomarkers in the areas of oncology, radiology, and discovery of cancer treatment solutions. He has published over 176 peer-reviewed journal/conference articles, 35 peer-reviewed clinical abstracts and 54 US/International patents, including 32 MICCAI papers, two of which have received the MICCAI Society Young Scientist Award runner-up (Harrison 2017) and Publication Impact Award (Roth 2018). Additionally, he was the main technical leader for two of the most-impactful public radiology image dataset releases (NIH ChestXray14, NIH Clinical Center Director’s Award; NIH DeepLesion 2018). He coauthored the highest-cited IEEE Trans. on Medical Imaging article and the highest-cited medical imaging CVPR paper in the last five years, with his collaborating postdoc fellows (Hoo-Chang Shin 2016, Xiaosong Wang 2017). Two of his publications received the RSNA Informatics Research Trainee Awards (Xiaosong Wang 2016, Ke Yan 2018). In addition to his extensive research and publication activities, Dr. Lu plays an active role in the leading societies of the computer vision and medical imaging fields. He is a long-standing member of the MICCAI Society, elevated IEEE Fellow class of 2021 for my contributions to machine learning for cancer detection and diagnosis, member of IEEE Signal Processing Society, and member of the IEEE Computer Society. He serves as an Associate Editor of IEEE Trans. on Pattern Analysis and Machine Intelligence, IEEE Signal Processing Journal. In 2017 and 2019, he co-edited two books on Deep Learning and Convolutional Neural Networks for Medical Image Computing by Springer-Nature. Dr. Lu was Area Chair for MICCAI in 2015, 2016, 2018 (having participated in most MICCAI conferences since 2011); IEEE CVPR in 2017, 2019, 2020, and 2021; and AAAI in 2019 and 2020, and won best reviewer awards at CVPR 2018, BMVC 2018 and NeurIPS 2020.