Events

Vincent Oh (AWS) – Build with Generative AI on AWS

Karthyek Murthy & Dai Gengling (Singapore University of Technology and Design) – Presentations by the Aviation Studies Institute

Bryan Low (AI Singapore) – Learning with Less Data: Automated Machine Learning and Bayesian Optimization

Cyber security and resilience are major challenges in our modern economies; this is why they are top priorities on the agenda of governments, security and defense forces, management of companies and organizations. Hence, the need of a deep understanding of cyber risks to improve resilience. We propose here an analysis of the database of the cyber complaints filed at the French Gendarmerie Nationale. We perform this analysis with a new algorithm developed for non-negative asymmetric heavy-tailed data, which could become a handy tool for applied fields, including operations research. This method gives a good estimation of the full distribution including the tail. Our study confirms the finiteness of the loss expectation, necessary condition for insurability. Finally, we draw the consequences of this model for risk management, compare its results to other standard EVT models, and lay the ground for a classification of attacks based on the fatness of the tail. This is a joint work with M. Dacorogna and N. Debbabi.

Heather VanCura (Oracle) – What Is MySQL, and Why Should You Learn it? and Santosh Panda (Cloudrea) – Building modern databases using object stores

Mok Sze Xin (Ernst & Young) – Technology and Data in the World of Commercial Trade and Supply Chains

Greater uncertainty in global trade flows and black swan events, such as COVID-19, have increasingly challenged the current supply chain business model. Digital technologies have been recognized as a key enabler for enabling resilient and responsive supply chains. In this seminar, the speaker will share about the ongoing research program Supply Chain 4.0, which aims to research and co-develop digital and automation technologies with industry members to enable responsive, resilient and secured supply chain management processes to prepare company for the ever volatile, uncertain, complex, and ambiguous (VUCA) global supply chain environment. Details of the three research themes will be shared, which include Supply Chain Connectivity, Data-Driven Optimization and Smart Warehouse Automation for next generation logistics.

Jonathan Tan (Unabiz) – Massive IoT: Tiny Sensors, Low Power Network, Unified Interface

Signs of Safety: Qualification Devices and the Consumption of Risky Poultry in China’s ‘Wet’ Markets

The nonparametric maximum likelihood estimation (NPMLE) is a classic and important method to estimate the mixture models from finite observations. The discretization of the infinite dimensional probability measure with a fixed support in the NPMLE leads to a finite dimensional convex optimization problem. Although can be solved by off-the-shelf interior point based solvers, the algorithm does not scale well with the number of grid points and the number of observed data points. In this talk, we propose an efficient and scalable semismooth Newton based augmented Lagrangian method (ALM). By carefully exploring the structure of the ALM subproblem, we show that the computational cost of the generalized Hessian (second order information) is independent of the number of grid points. Extensive numerical experiments are conducted to show the effectiveness of our approach.