Angelica I Aviles Rivero

Assistant Professor, Tsinghua University

Angelica’s research focuses on the intersection of computational mathematics, inverse problems, and machine learning, with a strong emphasis on addressing large-scale, real-world challenges. She develops novel algorithmic approaches capable of processing vast amounts of data, particularly by integrating machine learning techniques with knowledge-driven models. Her work centres on hybrid techniques that combine data-driven insights with physical and geometric constraints, such as variational models enhanced by machine learning, enabling more efficient and accurate analysis of large and complex data. 

Her research interests include, but are not limited to:  Inverse Problems, AI4Science (Learned PDEs), Graph Learning, LLM4Science and Math4Healthcare.

Fore more details visit: https://angelicaiaviles.wordpress.com/