William Lotter Wins Prestigious Awards in Oncology and Radiology
Dr. William (Bill) Lotter, PhD, a leading researcher in artificial intelligence (AI) for medical imaging, has been honored with three prestigious accolades for his contributions to oncology and radiology.
Dr. Lotter was named one of the recipients of the Wong Family Awards in Translational Oncology for FY25 for his innovative project, “Bridging spatial biology with routine histopathology using AI to improve cancer prognostication.” His work will study the tumor microenvironment by combining spatial biology data with conventional histopathology using AI, paving the way for more accurate and actionable cancer prognoses. This award goes to advancing the careers of early career investigators as they pursue innovative projects in clinical and/or translational oncology, biotechnology development, precision medicine, or immunotherapy approaches.
In addition, Dr. Lotter has been named to the Radiology Business Forty Under 40 Class of 2024, a distinguished list highlighting emerging leaders under 40 who are driving innovation and progress in the field of radiology. The recognition underscores the impact of his efforts in using AI to enhance medical imaging and diagnostic practices.
Furthermore, Dr. Lotter has received a Trailblazer Award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB) for his proposal “Improving prognosis prediction and therapy selection for cutaneous squamous cell carcinomas using artificial intelligence.” His project will leverage AI to more accurately identify aggressive cutaneous squamous cell carcinomas, a type of skin cancer, to guide treatment selection. Trailblazer Awards are designed to fund early career investigators for high-risk, high-reward projects at the interface of quantitative and biomedical sciences.
Dr. Lotter is an Investigator in the Department of Data Science at the Dana-Farber Cancer Institute and Assistant Professor at the Harvard Medical School, where he focuses on integrating computational methodologies with medical imaging to improve patient outcomes. His honors showcase his dedication to bridging technology with clinical impact, where his work highlights the transformative potential of AI in medicine.
