Greg Buzzard, Professor of Mathematics
Much of my recent work is joint with Charlie Bouman in Purdue ECE. We've developed methods for dynamic sampling and reconstruction with a variety of sensing modalities. At a more fundamental level, we've developed the foundations of the Plug and Play method for image reconstruction into a formulation we call Consensus Equilibrium, which gives a principled framework for reconciling sensing data and external information, such as a preferred denoising method, even when one or both of these information sources is not easily cast in an optimization framework.
- SIAM Imaging Sciences Best Paper Prize 2020
- Best Paper Prize Lecture: Plug and Play and MACE Explained
- Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation
- Multi-Agent Consensus Equilibrium (MACE): the problem formulation behind Plug-and-Play
- Full CV - pdf version
MA 544 Real Analysis And Measure Theory
Neural networks course (Spring 2019):
MA 59800 Mathematical Aspects of Neural Networks
Resources for online teaching
- Math Department Teaching Info
- Purdue’s page on teaching remotely
- Purdue's page on the use of various online tools
- The Math Department page on online teaching practices for Spring 2020
- Email for tehcnical help at firstname.lastname@example.org
- Computational Imaging XIX, January 18-29, 2021
- Approximation Theory and Machine Learning,
Purdue University, September 29 - 30, 2018
Slides and videos are available through the link above.
- The case for basic research by Eric Lander at the National Math Festival in 2015.
- Mathematics: 1,000 Years Old, and Still Hot
- What can I do with a major in... MATHEMATICS?
- Other interesting links.
email@example.com | 400 MATH | 765-496-5026
150 N. University St. | West Lafayette, IN 47907-2067