Series Editor 

Luca Calatroni is a permanent junior research scientist of the French Centre of Scientific Research (CNRS) at the laboratory I3S of Sophia-Antipolis, France. He got his PhD in applied mathematics in 2016 as part of the Cambridge Centre for Analysis (DTC) and he worked as post-doctoral research fellow at the École Polytechnique (Palaiseau, France) with a Lecteur Hadamard fellowship funded by the FMJH. His research interests include variational models for mathematical imaging, inverse problems, non-smooth and non-convex optimization with applications to biomedical imaging, computational neurosciences and digital art restoration.

Editorial Board

Martin Burger is Professor of Applied Mathematics at the Department of Mathematics, Friedrich-Alexander University Erlangen-Nürnberg. His interests include nonlinear partial differential equations, inverse problems, and variational techniques in imaging. In particular, he is known for the development and mathematical analysis of nonlinear regularization methods for inverse and imaging methods. His further interests include the development of mathematical models in life and social sciences, which together drive interdisciplinary research developments, e.g., in biomedical imaging. Martin Burger has received several awards and honors for his scientific contributions, such as the Calderon prize for distinguished contributions in the field of inverse problems. He serves on editorial boards of several journals and is one of the editors-in-chief of the European Journal of Applied Mathematics.

Raymond Chan is Vice-President (Student Affairs) at City University of Hong Kong and the co-Director of the Hong Kong Centre for Cerebro-Cardiovascular Health Engineering. He has served on the editorial boards of many journals, including Asian Journal of Mathematics (co-Chief Editor), Advances in Computational Mathematics, Journal of Mathematical Imaging and Vision, Journal of Scientific Computing, SIAM Journal on Imaging Sciences, and SIAM Journal on Scientific Computing. He was elected a Fellow of the US Society of Industrial and Applied Mathematicians in 2013 and a Fellow of the American Mathematical Society in 2021. He is now on the SIAM Board of Trustees. Since 2006, he has been the Vice-President of the International Consortium of Chinese Mathematicians.

Ekaterina Rapinchuk is Assistant Professor in the Department of Mathematics and the Department of Computational Mathematics, Science and Engineering at Michigan State University. Prior to this appointment, she was a UC President's Postdoctoral Scholar at University of California, San Diego. Her research involves developing new graph-based semi-supervised learning methods, especially those designed for very low amounts of labeled data, which is often scarce for many applications. She is particularly interested in the data classification task of machine learning, a crucial task found in many practical applications, such as medical diagnosis. Some applications of her methods include hyperspectral data, biological/medical data and image data.

Carola-Bibiane Schönlieb is Professor of Applied Mathematics at the University of Cambridge. There, she is Head of the Cambridge Image Analysis group and co-Director of the EPSRC Cambridge Mathematics of Information in Healthcare Hub. She has been a fellow of Jesus College Cambridge since 2011 and a fellow of the Alan Turing Institute, London since 2016. She also holds the Chair of the Committee for Applications and Interdisciplinary Relations (CAIR) of the EMS. Her current research interests focus on variational methods, partial differential equations and machine learning for image analysis, image processing and inverse imaging problems. She has active interdisciplinary collaborations with clinicians, biologists and physicists on biomedical imaging topics, chemical engineers and plant scientists on image sensing, as well as collaborations with artists and art conservators on digital art restoration.

Daniel Tenbrinck is Lecturer in the Department of Mathematics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Main Coordinator of the MSCA RISE action Nonlocal Methods in Arbitrary Data Sources (NoMADS), which lay the foundation for this Elements series. In 2020 he became the study course coordinator for the newly established B.Sc./M.Sc. Data Science study programmes at FAU. His research interests are focused on the translation of variational methods and PDEs to graphs and hypergraphs, as well as mathematics of machine learning.

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