Undergraduate Student
Stanford University
Ethan Farah is a Biomechanical Engineering and Computer Science undergraduate at Stanford University (Class of 2026) with a focus on artificial intelligence applications in medicine. He combines rigorous coursework in machine learning, deep learning, and decision-making theory with biomechanics and fluid mechanics theory.
As an undergraduate researcher in Dr. Alison Marsden's lab at Stanford, Ethan specializes in computational fluid dynamics modeling for cardiovascular applications using SimVascular. His current research includes co-authoring a study on the hemodynamic performance of the newly approved TAMBE thoracoabdominal multi-branched endoprosthesis, analyzing patient-specific flow dynamics and wall shear stress patterns in renovisceral branches. He is also leading novel research on stroke risk prediction in asymptomatic carotid arteries using reinforcement learning frameworks applied to arterial rheology.
Ethan's interdisciplinary research experience spans multiple fields: investigating mechanical properties of the Stentor coeruleus's self-healing in the Tang Group, exploring scaffold proteins and cardiac remodeling in the Kapiloff Lab, and developing machine learning approaches for myocyte detection and segmentation. His technical expertise encompasses proficiency in C++, C, Python, and advanced computational modeling techniques.
Beyond academic research, Ethan will join Optiver's quantitative trading systems team as a software engineering intern in summer 2025, applying his algorithmic studies to financial markets. He also founded EZMathTutors, a free peer-to-peer tutoring platform serving over 40 students.
Ethan's work represents the convergence of computational medicine and personalized healthcare, with a commitment to developing equitable algorithmic solutions for complex medical challenges.