Numerical Techniques for Solving Ill-posed Problems and Their Applications : IWAMML'25, Beni Mellal, Morocco, December 2–3

The Inaugural International Workshop on Applied Mathematics and Machine Learning aspires to convene a distinguished assembly of scientists, scholars, and innovators dedicated to advancing the frontiers of mathematical inquiry and its transformative applications across diverse scientific realms.

The Inaugural International Workshop on Applied Mathematics and Machine Learning aspires to convene a distinguished assembly of scientists, scholars, and innovators dedicated to advancing the frontiers of mathematical inquiry and its transformative applications across diverse scientific realms. This prestigious gathering seeks to illuminate the latest developments in mathematical modeling, computational techniques, and their synergistic interplay with machine learning, fostering a vibrant exchange of ideas that bridges theoretical rigor with practical impact. The workshop will delve into a constellation of pivotal themes, including Inverse Problems, Partial Differential Equations, Mathematical Control, Numerical Analysis, and Computer Science. A particular emphasis will be placed on the burgeoning domain of inverse problems, whose integration with computer science remains a fertile yet underexplored frontier. Despite its rapid evolution, this field has yet to be fully anchored by robust mathematical frameworks—a gap this event is poised to address through rigorous exploration and insightful discourse. Our ambition is to deliver profound mathematical insights paired with expressive, accurate applications that resonate across disciplines. By spotlighting emerging trends and fostering interdisciplinary collaboration, the workshop aims to catalyze innovative solutions that harness the power of mathematics to tackle complex challenges in science and industry. The growing prominence of these topics in both academic discourse and industrial innovation ensures that this event will captivate a diverse audience, from mathematicians and computer scientists to engineers and industry leaders.