Regression and Fitting Methods on Manifold-Valued Data

Ines ADOUANI received her PhD in complex analysis and Finsler geometry from the University of Pierre and Marie Curie, France, in 2015. Since then, she has been serving as an Assistant Professor at the Institute of Applied Sciences and Technology of Sousse, Tunisia. Additionally, from 2020 to 2021, she held a position as an Assistant Professor at King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. Her main research interests encompass complex geometry (including Finsler and Kähler geometry), optimization on Riemannian manifolds, regression, and fitting on Riemannian manifolds, as well as their applications to computer vision and medical imaging problems.

Chafik SAMIR received his PhD on learning and analysis of shapes and patterns in 2007 at the University of Lille, France. After spending two years as a postdoc working on manifolds and related applications at UCL, he joined UCA in 2009. His main research interests are machine learning for manifold-valued data, such as functional and medical observations, optimization of loss functions, statistical shape analysis, spatio-temporal patterns and fusion, regression and fitting on Riemannian manifolds, and their applications to real-world problems.

Ines ADOUANI於2015年在法國皮埃爾與瑪麗居里大學獲得複雜分析和Finsler幾何的博士學位。自那時起，她一直擔任突尼西亞蘇斯應用科學與技術研究所的助理教授。此外，從2020年到2021年，她在沙烏地阿拉伯達蘭的法赫德石油與礦業大學擔任助理教授。她的主要研究興趣包括複雜幾何（包括Finsler和Kähler幾何）、在黎曼流形上的優化、回歸以及在黎曼流形上的擬合，並將其應用於計算機視覺和醫學影像問題。

Chafik SAMIR於2007年在法國里爾大學獲得有關形狀和模式學習與分析的博士學位。在UCL擔任兩年的博士後研究員，專注於流形及相關應用後，他於2009年加入UCA。他的主要研究興趣是針對流形值數據的機器學習，例如功能性和醫學觀察、損失函數的優化、統計形狀分析、時空模式與融合、在黎曼流形上的回歸與擬合，以及這些技術在現實世界問題中的應用。