Wang Guanyi

Wang Guanyi is an Assistant Professor in the Department of Industrial Systems Engineering and Management at the National University of Singapore (NUS). He is affiliated with the Institute of Operations Research and Analytics (IORA), part of NUS’s Smart Nation Research Cluster. His research focuses on Mixed Integer Programming, Nonlinear Optimization, and Statistical Learning with applications in Machine Learning. Guanyi holds a Ph.D. from Georgia Institute of Technology (2016–2022), advised by Prof. Santanu S. Dey, an M.S. from Johns Hopkins University (2014–2016), advised by Prof. Amitabh Basu, and a B.S. from University of Science and Technology, Beijing (2010–2014).

His work bridges optimization theory and machine learning, with notable contributions to sparse principal component analysis (PCA), algorithm design for high-dimensional problems, and approximation algorithms for mixed-integer nonlinear optimization. Recent research trends include adversarial robustness in PCA, fair decision-making frameworks, and efficient stochastic optimization methods.

Guanyi’s publications appear in top-tier journals like Mathematical Programming, Operations Research, and IEEE Transactions on Signal Processing. He has developed novel algorithms for sparse regression, group sparsity regularization, and neural network pruning. His research emphasizes both theoretical guarantees and practical computational efficiency.