Fabiana Zama

Associate professor since 2006, she carries out her research on optimization and regularization methods for inverse problems. Development of sophisticated multi-penalty regularization techniques for linear ill-posed inverse problems, with particular focus on uniform multipenalty approaches and automatic parameter selection algorithms. Recent work includes scaled gradient projection methods and pixel-wise multi-penalty approaches for various applications including image restoration and geophysical parameter estimation.