Convex Optimization in Radiation Therapy Treatment Planning
Algorithms for Large-Scale Computation in Medicine and Health
Structured Linear Algebra, Matrix-Free Algorithms, and General-Purpose Numerical Solvers
A convex optimization approach to radiation treatment planning with dose constraints. *A. Fu, *B. Ungun, L. Xing, and S. Boyd, Optimization and Engineering, 2019
Real time radiation treatment planning with optimality guarantees via cluster and bound methods. B. Ungun, L. Xing, and S. Boyd, INFORMS Journal on Computing, Accepted 2018
Optimization of rotational arc station parameter optimized radiation therapy. P. Dong, B. Ungun, S. Boyd, and L. Xing, Medical Physics, 2016
Nanofabricated upconversion nanoparticles for photodynamic therapy. B. Ungun, R. Prud’homme, S. Budijono, J. Shan, S. Lim, Y. Ju, and R. Austin, Optics Express, 2009
Nanoparticles for photodynamic therapy. R. Prud’homme, M. Gindy, B. Ungun, and Y. Liu, United States Patent Application 20110022129
PhD Candidate, Biongineering, Stanford, 2012–Present.
MD Candidate, School of Medicine, Stanford, 2010–Present.
MS, Bioengineering, Stanford, 2014.
BS magna cum laude, Chemical Engineering, Princeton, 2008.
Stanford, Salisbury Robotics Laboratory, Graduate Research, 2012–2014.
Princeton, Robert K. Prud'homme Research Group, Undergraduate Research, 2006–2008.
BD Biosciences Fluidics group, Internship, Summer 2007.
Bloom Energy, Internship, Summer 2005 and 2006.
Stanford Bio-X Bowes Fellow, 2014–2018.
Calvin Dodd MacCracken Award for Senior Thesis/Project Award, Princeton School of Engineering & Applied Sciences, 2008.
Procter & Gamble Award for Outstanding Design Project, Princeton Department of Chemical Engineering, 2008.