Lars Ruthotto

Lars Ruthotto

Winship Distinguished Research Associate Professor of Mathematics and Computer Science

Emory University, Atlanta, GA, USA

Biography

I am an applied mathematician developing computational methods for machine learning and inverse problems. I am a Winship Distinguished Research Associate Professor in the Department of Mathematics and the Department of Computer Science at Emory University and a member of Emory’s Scientific Computing Group. I lead the Emory REU/RET site for Computational Mathematics for Data Science. 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 by grants from the US NSF and the Office of Naval Research. Previously, I was supported by the US Department of Energy’s Advanced Scientific Computing Research program, the Air Force Office of Scientific Research, contracts by Sandia National Laboratories, the US Israeli Binational Science Foundation, and the Centers for Disease Control.

Interests

  • Scientific Computing
  • Optimization
  • Machine Learning
  • Inverse Problems
  • Image Registration

Education

  • PhD in Mathematics, 2012

    University of Münster, Germany

  • Diploma in Mathematics, 2010

    University of Münster, Germany

Research

My research and teaching sit at 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. I also develop machine learning approaches for solving high-dimensional partial differential equations and optimal control problems and am interested in connections to active and reinforcement learning.

In inverse problems, I have been working on using generative modeling for inference. Over the years, I have been working 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.

Teaching

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. I also taught a short short course on Deep Generative Modeling as part of the Spring School on Data and Models at the University of South Carolina.

Selected Activities

Team

  • Nicole Yang Distinguished Visiting Assistant Professor, since Sept. 2022
  • Haley Rosso, Computational Mathematics PhD, since Jan 2022
  • Katie Keegan, Computational Mathematics PhD, since Sep 2024

Contact

  • lruthotto@emory.edu
  • 400 Dowman Drive, Atlanta, GA 30322
  • Office W408, located in the 4th floor in the Math and Science Center
  • By appointment (please email me)