Bennett Landman
About Bennett Landman
Bennett Landman is a Chancellor Faculty Fellow and Associate Professor at Vanderbilt University, specializing in medical imaging and statistical inference.
Chancellor Faculty Fellow at Vanderbilt University
Since July 2019, Bennett Landman has been serving as a Chancellor Faculty Fellow at Vanderbilt University in Nashville, Tennessee. In this role, he continues to contribute to the academic environment through teaching, research, and mentorship. His work focuses on the integration of advanced imaging techniques and statistical inference to improve medical imaging.
Academic and Professional Background
Bennett Landman has an extensive academic and professional background. He began his career as a Graduate Researcher at Johns Hopkins School of Medicine from 2004 to 2008. Subsequently, he served as an Assistant Research Professor at Johns Hopkins University from 2008 to 2009. In 2009, he joined Vanderbilt University as an Assistant Professor, a position he held until 2016. He then became an Associate Professor and continues to serve in this capacity. He is also a Partner at Silver Maple.
Educational Qualifications
Bennett Landman has a robust educational background. He earned his Bachelor of Science in Electrical Engineering and Computer Science from 1997 to 2001. He went on to achieve a Master of Engineering in Electrical Engineering and Computer Science in 2001-2002. Later, he completed his Doctor of Philosophy in Biomedical Engineering from The Johns Hopkins University School of Medicine between 2004 and 2008.
Research Focus and Contributions
Bennett Landman leads the Medical-image Analysis and Statistical Interpretation (MASI) Lab. His research aims to leverage population imaging studies to improve the understanding of individual anatomy for personalized medicine. He focuses on label fusion, statistical segmentation, robust multi-modal inference methods, and high-throughput quality control for medical imaging. His work also involves machine learning models and clinical studies aimed at interpreting medical imaging data.
Technical Skills and Interests
Bennett Landman's expertise includes medical imaging, image processing, and statistical inference. He specializes in working with complex, high-dimensional, and under-sampled spaces using empirical data. He also has a strong background in AI, Python, and imaging data analysis. His interest in advanced imaging techniques drives his research and development efforts, particularly in the context of personalized medicine.