## Who am I? (abridged version)

- Name is pronounced Yeh-or-yee-os, but I'll accept George(ous)
- Born and raised in Cyprus, before heading to Boston for (u)grad
- Into musical theatre, camping, and generative art

- 2nd year Miller fellow
- Co-hosted by Prof. Mary Scott (MSE) and Prof. Joel Moore (Physics)

- Interested in imaging fields (temperature, magnetization, current density) inside materials w/ high resolution
- This is a high-dimensional, non-convex, inverse problem

## Non-convex inverse problems (aka Sudoku for dummies)

- Sudoku is a constraint satisfaction problem:
- Each row contains only one of each of the numbers 1-9
- Each column contains only one of each of the numbers 1-9
- Each 3x3 block contains only one of each of the numbers 1-9
- Solution must be consistent with a (minimum) set of pre-defined clues

- Each constraint can be interpreted as a projection to a non-convex set
- This can now be solved using iterative proximal gradient algorithms

- iteration 01
- iteration 02
- iteration 03
- iteration 04
- iteration 05
- animated solution