School of Engineering
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Drew Endy
Associate Professor of Bioengineering and Senior Fellow, by courtesy, at the Hoover Institution and at the Freeman Spogli Institute for International Studies
Current Research and Scholarly InterestsWe work to strengthen the foundations and expand the frontiers of synthetic biology. Our foundational work includes (i) advancing reliable reuse of bio-measurements and -materials via standards that enable coordination of labor, and (ii) developing and integrating measurement and modeling tools for representing and analyzing living matter at whole-cell scales. Our work beyond the frontiers of current practice includes (iii) bootstrapping biotechnology tools in unconventional organisms (e.g., mealworms, wood fungus, skin microbes), and (iv) exploring the limits of whole-genome recoding and building cells from scratch. We also support strategy and policy work related to bio-safety, security, economy, equity, justice, and leadership.
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Daniel Bruce Ennis
Professor of Radiology (Veterans Affairs) and, by courtesy, of Bioengineering
Current Research and Scholarly InterestsThe Cardiac MRI Group seeks to invent and validate methods to quantify cardiac performance. We develop methods to measure cardiac structure (DWI/DTI), function (tagging and DENSE), flow (PC-MRI), and remodeling (diffusion, T1-mapping, fat-water mapping) for pediatrics and adults.
Fundamental to our research is a set of tools for numerically optimizing gradient waveforms, Bloch simulations, and patient-specific 3D-printed cardiovascular structures connected to computer controlled flow pumps. -
Amir Esrafilian
Visiting Postdoctoral Scholar, Bioengineering
Affiliate, Wu Tsai Human Performance AllianceBioAmir Esrafilian, PhD, focuses on computational biomechanics and mechanobiology, with an emphasis on multiscale and multiphysics modeling of the musculoskeletal system and lower-limb joints.
His work integrates musculoskeletal and finite element modelling, medical imaging, motion analysis, electromyography, and artificial intelligence to better understand human movement, joint mechanics, and the development and progression of musculoskeletal disorders such as osteoarthritis. A particular focus of his research is developing automated and data-driven computational frameworks that connect patient-specific anatomy, movement, muscle coordination, and tissue-level biomechanics.
Amir's research aims to translate advances in computational modelling and machine learning into clinically relevant tools for understanding disease mechanisms, identifying biomarkers, and supporting personalised prevention and treatment strategies.
Contact info: amires@stanford.edu
