NUS National Observance Ceremony 2019

University Hall National University of Singapore, 21 Lower Kent Ridge Rd, Singapore

IORA took part in NUS National Day Observance Ceremony held on Thursday, 8 August 2019 at University Hall, National University of Singapore. Dr Huang Jinjia, IORA Research Fellow, presented the  SDPNAL+ software. The software SDPNAL+ is designed for solving semidefinite programming (SDP), an important subfield of mathematical optimization and its applications are growing rapidly. Many […]

INFORMS 2019

The 2019 INFORMS Annual Meeting is a unique opportunity to connect and network with the more than 6,000 INFORMS members, students, prospective employers and employees, and academic and industry experts who compose the INFORMS community. It is with great pleasure to share the presentations and awards of IORA faculty, students at the INFORMS 2019 conference that took place in Seattle. Professor Teo […]

IORA Seminar Series | 15 Jan | 10am

Shape-constrained convex regression problem deals with fitting a convex function to the observed data, where additional constraints are imposed, such as component-wise monotonicity and uniform Lipschitz continuity. This talk presents a unified framework for computing the least squares estimator of a multivariate shape-constrained convex regression function in $mathbb{R}^d$. We prove that the least squares estimator […]

IORA Seminar Series | 26 Feb | 10am

Extensive research has shown that human decision makers in operations and supply chains are often influenced by cognitive biases and social preferences, and as a consequence fail to achieve the optimal performance prescribed by normative operations theories.  In this talk, we will discuss how behavioral factors affect decisions and economic outcomes in two operations management […]

The Dao of Robustness

We present a general framework for data-driven optimization called robustness optimization that favors solutions for which a risk-aware objective function would best attain an acceptable target even when the actual probability distribution would deviate from the empirical distribution.  Unlike data-driven robust optimization approaches, the decision maker does not have to size the  ambiguity set, but […]