Dr. McKell Woodland is a deep learning researcher and educator. Her research primarily focuses on out-of-distribution detection for medical imaging segmentation models, with a secondary focus on generative modeling evaluation in medical imaging. She has published her work in venues such as the MELBA journal and the MICCAI conference, where she won the "Best Spotlight Paper" award at the associated UNSURE workshop.
Dr. Woodland holds a Ph.D. in Computer Science from Rice University and a B.S. in Applied and Computational Mathematics from Brigham Young University. She currently works as a data scientist at MD Anderson Cancer Center in the Morfeus lab. She has previously held data science internships at Microsoft, Lawrence Livermore National Laboratory, 3M Health Information Systems, and the U.S. Department of Defense.
Outside of research, Dr. Woodland is passionate about computer science education for those in all walks of life. She has taught and mentored hundreds of students, ranging from elementary schoolers to professors, through The Coding School, Brigham Young University - Idaho, the Summer STEM Institute, and Rice University. Dr. Woodland founded the Kids Who Code organization at Brigham Young University and currently serves on the Young Professional Advisory Board for The Coding School.