AI / Machine Learning Engineer
Dana-Farber Cancer Institute
Thomas Sounack is a data scientist and machine learning engineer working at the Dana-Farber Cancer Institute, where he focuses on applying AI to clinical and biomedical research. His work spans natural language processing, representation learning, and scalable machine learning systems, with a particular emphasis on clinical text analysis and reproducible modeling. Thomas holds an MSc in Mechanical Engineering from Stanford University with a concentration in AI, and collaborates closely with clinicians and informatics teams to develop methodologies for real-world medical applications.
Using a Large Language Model to Assess Documentation of Electronically Reported Symptoms in Oncology
Saturday, March 7, 2026
8:30am - 9:30am PST
Disclosure(s): No financial relationships to disclose