Boumediene Hamzi

Boumediene Hamzi is a Senior Scientist at the California Institute of Technology (Caltech) in the Department of Computing and Mathematical Sciences. He is also an Affiliate Fellow of the Data Science Institute at Imperial College London and an External Researcher at the Alan Turing Institute (London, UK). His career includes prestigious roles such as Marie Curie Fellowships and visiting professorships at institutions like Johns Hopkins University.

• Senior Scientist, Caltech (current)
• Affiliate Fellow, Data Science Institute, Imperial College London
• External Researcher, Alan Turing Institute
• Marie Curie Fellow, Imperial College London (twice)
• Marie Curie Fellow, Yıldız Technical University and Koç University

His research bridges Machine Learning (ML), Dynamical Systems Theory (DST), and Algorithmic Information Theory (AIT), aiming to develop a theoretical framework for ML. Key directions include:

• ML for Dynamical Systems: Analyzing systems via data in reproducing kernel Hilbert spaces.
• DST for ML: Using dynamical systems tools to understand ML algorithms.
• ML for AIT: Approximating Kolmogorov Complexity for compression and prediction.
• AIT for ML: Explaining ML applicability using AIT tools.

He co-leads the Alan Turing Institute's Research Interest Group on "Machine Learning and Dynamical Systems" and co-organizes the One World Seminar Series on the Mathematics of Machine Learning. His work addresses challenges in modeling climate dynamics, biological systems, and complex domains.

Scientific Awards

• Marie Curie Fellow (Imperial College London, Yıldız Technical University, Koç University)

Hamzi has organized multiple international symposia and workshops on ML, DST, and AIT intersections, including events at Imperial College London, Fields Institute, and the Alan Turing Institute.