Dr. Holden Wu is a Professor in the Departments of Radiological Sciences and Bioengineering at the University of California Los Angeles (UCLA). He is also a Member of the Jonsson Comprehensive Cancer Center and the California NanoSystems Institute. He completed his B.S. in Electrical Engineering at National Taiwan University in 2003, his M.S. in Electrical Engineering at Stanford University in 2005, and his Ph.D. in Electrical Engineering at the Magnetic Resonance Systems Research Lab at Stanford University in 2009. He finished his postdoctoral training in Cardiovascular MRI at Stanford University and joined the UCLA Department of Radiological Sciences in 2012. Dr. Wu is interested in developing rapid and robust quantitative magnetic resonance imaging (MRI) techniques for improving the diagnosis and treatment of cancer and metabolic diseases. His group focuses on technical developments in MRI pulse sequence design, accelerated data acquisition, image reconstruction algorithms, artificial intelligence methods, and quantitative data analysis. These advanced techniques are used to improve early detection of disease, characterize the disease state, facilitate treatment planning, guide interventions, assess treatment efficacy, and perform monitoring.
Dr. Holden Wu is a Professor in the Departments of Radiological Sciences and Bioengineering at the University of California Los Angeles (UCLA). He is also a Member of the Jonsson Comprehensive Cancer Center and the California NanoSystems Institute. He completed his B.S. in Electrical Engineering at National Taiwan University in 2003, his M.S. in Electrical Engineering at Stanford University in 2005, and his Ph.D. in Electrical Engineering at the Magnetic Resonance Systems Research Lab at Stanford University in 2009. He finished his postdoctoral training in Cardiovascular MRI at Stanford University and joined the UCLA Department of Radiological Sciences in 2012. Dr. Wu is interested in developing rapid and robust quantitative magnetic resonance imaging (MRI) techniques for improving the diagnosis and treatment of cancer and metabolic diseases. His group focuses on technical developments in MRI pulse sequence design, accelerated data acquisition, image reconstruction algorithms, artificial intelligence methods, and quantitative data analysis. These advanced techniques are used to improve early detection of disease, characterize the disease state, facilitate treatment planning, guide interventions, assess treatment efficacy, and perform monitoring.