Join us on Thursday, March 19, 2026, at 12:00 PM PT/3:00 PM ET for the lecture: “Multimodal Deep Learning Models for Thyroid Cancer Risk Stratification” by Dr. William Speier. This lecture is part of the Bridge2AI Training, Recruitment, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module.

Dr. William Speier is an Associate Professor in the Departments of Radiology, Bioengineering, and Bioinformatics at UCLA and a member of the Medical Informatics home area. He is the Associate Director of the UCLA Biomedical Artificial Intelligence Research (BAIR) Laboratory, where his research focuses on developing machine learning and AI methods to improve clinical support applications, including brain-computer interface assistive devices and automated pipelines for limbal stem cell deficiency diagnosis. His work integrates large language models, statistical modeling, system optimization, and evaluation metrics, with a strong emphasis on translating computational methods into real-world clinical implementation.

Dr. Speier serves as Co-chair of the Medical Informatics Curriculum Committee and on the Steering Committee for the Brain Info Conference. He is an Academic Editor for Frontiers in Human Neuroscience (since 2023) and PLOS ONE (since 2018), and has contributed as a mentor in the UCLA CARE Science, Engineering, and Math (SEM) Summer Program (2019) and the Bruins-In-Genomics (BIG) Mentorship Program (2019-20). His research highlights a commitment to translational science, combining theoretical development with online implementation and patient testing.

Lecture Learning Objectives:

• Explain the importance of type 1 error in thyroid cancer diagnosis.
• Compare different approaches to handle multi-modal data.
• Evaluate the effectiveness and clinical utility of biomedical AI applications.

Introduction