Andre Milzarek is an assistant professor at Instutitute for Data and Decision Analytics, The Chinese University of Hong Kong, Shenzhen starting from April 1, 2019. Before that, he was a postdoctoral researcher at the Beijing International Center for Mathematical Research at the Peking University in Beijing. He received his master's degree with honours and his doctoral degree in mathematics from the Technical University of Munich in Germany under the supervision of Michael Ulbrich in 2013 and 2016, respectively. His main research directions and interests cover nonsmooth optimization, large-scale and stochastic optimization, second order methods and theory. From 2010 to 2012 he was supported by the Max-Weber program of the state of Bavaria and in 2017 he received the Boya Postdoctoral Fellowship at Peking University.
PEER-REVIEWED JOURNAL PAPERS
1. Z. Wen, A. Milzarek, M. Ulbrich, and H. Zhang: Adaptive Regularized Self-Consistent Field Iteration with Exact Hessian for Electronic Structure Calculation, SIAM J. Sci.Comput., 35 (2013), pp. A1299-A1324
2. A. Milzarek and M. Ulbrich: A Semismooth Newton Method with Multi-Dimensional Filter Globalization for `1-Optimization, SIAM J. Optim., 24 (2014), no.1, pp. 298-333
3. J. Hu, A. Milzarek, Z. Wen, and Y. Yuan: Adaptive Quadratically Regularized Newton Method for Riemannian Optimization, SIAM J. Matrix Anal. & Appl., 39 (2018), pp.1181-1207
1. A. Milzarek, X. Xiao, S. Cen, Z. Wen, and M. Ulbrich: A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization, submitted to SIAM J.Optim. (April 2018)
2. A. Milzarek, X. Xiao, S. Cen, Z. Wen, and M. Ulbrich: On the Local Convergence of a Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization, submitted to SIAM J. Optim. (June 2018)
1. A. Milzarek: Numerical Methods and Second Order Theory for Nonsmooth Problems, Technical University of Munich, January 2016