Rate My Professor Zhiqiang Xu

Zhiqiang Xu is Assistant Professor of Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). He earned his Ph.D. in Computer Engineering from Nanyang Technological University in Singapore. Before joining MBZUAI, he worked as a senior research scientist at Baidu Research in China and gained industrial experience in automatic optical inspection for TFT-LCD panels and solar wafers as well as data analytics for airlines and insurance companies. Professor Xu serves as a reviewer for NeurIPS, ICML, ICLR, IJCAI, and AAAI.

His research interests lie at the intersection of numerical computation, stochastic optimization, and Riemannian optimization. He is also interested in deep learning, clustering, community detection, and topic modeling. Recent ongoing works include faster alternating least-squares for canonical correlation analysis, a comprehensively tight analysis of gradient descent for principal component analysis, accelerated inexact power methods, and Riemannian search for eigenvector computation. Key publications include “Faster Noisy Power Method” (ALT 2022), “A Comprehensively Tight Analysis of Gradient Descent for PCA” (NeurIPS 2021), “On the Riemannian Search for Eigenvector Computation” (JMLR 2021), “On the Faster Alternating Least-Squares for CCA” (AISTATS 2021), “Towards Practical Alternating Least-Squares for CCA” (NeurIPS 2019), and “Gradient descent meets shift-and-invert preconditioning for eigenvector computation” (NeurIPS 2018). His research group at MBZUAI conducts theory and applied research spanning machine learning, optimization, and statistics.