Anders Hansen

Professor Anders C. Hansen is a mathematician at the University of Cambridge and University of Oslo, leading the Applied Functional and Harmonic Analysis group. His work bridges functional analysis, artificial intelligence, and computational mathematics, focusing on the Solvability Complexity Index (SCI) hierarchy and stability issues in deep learning. He has held prestigious fellowships, including a Royal Society University Research Fellowship and Peterhouse Bye-Fellowship.

• Educated at the University of Cambridge, UC Berkeley, and the Norwegian University of Science and Technology
• Developed groundbreaking theories in compressed sensing and deep learning, revealing algorithmic instability paradoxes
• Organized workshops on computational mathematics and AI interpretability

His research explores the SCI hierarchy, exposing computational barriers in AI, quantum mechanics, and inverse problems. Key projects include Smale’s 18th problem and analyzing neural network stability. His work has transformed understanding of compressed sensing, particularly in medical imaging.

Recent scientific awards include the Whitehead Prize (2019), IMA Prize (2018), and Leverhulme Prize (2017). Collaborations span institutions like Caltech, MIT, and the University of Vienna.

As an educator, he teaches NST Part IA Mathematical Methods, Part II Numerical Analysis, and a Part III course on Compressed Sensing. His group has mentored 17 PhD and postdoctoral researchers since 2012.