Summary
Clara Sorensen is an AI specialist in biomedical research with a decade of experience building ML-driven biomarkers and imaging pipelines for neurodegenerative diseases across industry and academia. She has led translational projects at Novartis, Genentech, Roche, MIT and UCSF, developing GNNs, deep learning segmentation tools, and PET-free MRI algorithms that accelerate detection and staging for Alzheimer’s, Parkinson’s and Huntington’s disease. Her work blends rigorous computational methods (PyTorch, TensorFlow, dimensionality reduction, explainable AI) with practical lab transitions—she spearheaded a MATLAB-to-Python migration and delivered ~100 custom image-analysis algorithms for pathologists. Notably, her plasma biomarker research at UCSF showed earlier detection of Alzheimer’s changes than PET and enabled an MRI-based tau staging approach that reduces reliance on costly PET scans. She mentors students, communicates complex science to clinical teams, and volunteers teaching adaptive sports—bringing empathy and real-world impact to her technical work.
10 years of coding experience
Doctor of Philosophy - PhD, Bioengineering (joint UCSF), Doctor of Philosophy - PhD, Bioengineering (joint UCSF) at University of California, Berkeley
Bachelor of Arts - BA, Computer Science and Biological Sciences, Bachelor of Arts - BA, Computer Science and Biological Sciences at Wellesley College
Doctor of Philosophy - PhD, Bioengineering (joint UCB), Doctor of Philosophy - PhD, Bioengineering (joint UCB) at University of California, San Francisco
Spanish, English