I am an applied mathematician developing computational methods for machine learning and inverse problems. I am an Associate Professor in the Department of Mathematics and the Department of Computer Science at Emory University and a member of the Scientific Computing Group. Prior to joining Emory, I was a postdoc at the University of British Columbia and I held PhD positions at the University of Lübeck and the University of Münster.
I received an NSF CAREER award and am also supported grants from the US Israeli Binational Science Foundation, the US Department of Energy’s Advanced Scientific Computing Research program, and the Air Force Office of Scientific Research. Previously, I was supported by the Centers for Disease Control.
PhD in Mathematics, 2012
University of Münster, Germany
Diploma in Mathematics, 2010
University of Münster, Germany
My research and teaching focus on the intersection of applied mathematics and data science, particularly deep learning and inverse problems.
In deep learning, I seek to create new insights and efficient training for continuous models based on ordinary and partial differential equations. Also, I develop machine learning approaches for solving high-dimensional partial differential equations and optimal control problems.
In inverse problems, I have been focusing on applications in image registration and reconstruction and computational techniques including optimal experimental design, uncertainty quantification, numerical optimization, multiscale and multigrid methods, and regularization. Over the years, I had many fruitful collaborations with domain-experts from public health, geophysics, and medical imaging.
I offer regular one-semester courses in applied mathematics as well as advanced courses, seminars, and workshops in my research area. As part of my NSF CAREER project, I have also developed a new graduate-level course on Numerical Methods for Deep Learning. I offered this class twice at Emory and gave short versions of the class at TU Berlin, University of Chemnitz, and Scuola Normale Superiore di Pisa.
Selection Committee, SIAM Activity Group on Linear Algebra Early Career Prize 2021
Program Committee, Conference on Mathematical and Scientific Machine Learning (MSML), since 2019
Senior Fellow, IPAM Long program on Machine Learning for Physics and the Physics of Learning, Fall 2019.
Secretary, SIAM Activity Group on Imaging Science, 2018-19
Senior Consultant, xtract.ai Technologies Inc., 2017-19