معرفی
Sixin Zhang is an Associate Professor at INP-Toulouse, specifically affiliated with the ENSEEIHT school. He holds a Ph.D. from the Courant Institute of Mathematical Sciences, New York University (2012), following undergraduate studies. His postdoctoral research spanned institutions including ENS Paris, Peking University, and IRIT in France. His research focuses on machine learning, optimization, signal/image processing, statistics, dynamical systems, and high-dimensional data analysis.
Key research areas include representation learning for recognition and inverse problems, optimization algorithms, and applications in industrial systems and astrophysics. He contributed to the development of the Kymatio library for scattering transforms and co-authored foundational work on transform learning in non-negative matrix factorization.
His work bridges theoretical mathematics with applied machine learning, including contributions to generative models, data assimilation networks, and optimization techniques for neural networks. Notable projects include the MeteoNet AI challenge and the RWST statistical framework for interstellar medium analysis.
