Wearable technology such as smartwatches has the potential to transform the management and control of infectious diseases. Smartwatches provide continuous data about an individual’s health (e.g., heart rate, sleep patterns,...
Cybermanufacturing enables the shared use of networked manufacturing infrastructure to deliver manufacturing resources on-demand while maximizing capacity utilization, reducing consumption of natural and material resources, and reducing costs to product...
In the quest to enable robots to perform everyday tasks in unstructured environments, tactile sensing plays a crucial role. Tasks that benefit from refined tactile perception include industrial manufacturing, domestic...
Eye tracking research has shown that teammates in complex systems often exhibit overlapping eye gaze during critical moments of operation. This finding has driven the development of a new emerging...
Li-ion batteries (LIBs) are widely used to power today’s portable electronics, electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs), and in utility scale battery energy storage systems (BESSs). High performance...
This talk showcases recent research on modeling and analyzing the geometric shapes of objects and long sequences of shapes, with applications in operations research. These applications include modeling human performance...
Human-centricity is one of the core values of Industry 5.0, motivated by several challenges encountered with Industry 4.0, including social and workforce heterogeneity. An increasing number of inexperienced users interacting with sophisticated technologies underscores the need for continuous and personalized interventions taking into account contextual factors and individual differences. Recent advances in wearable and physiological...
University environments are becoming more dynamic and diverse than ever before. The landscape in industrial engineering continues to change rapidly and students and faculty in the discipline are called upon...
In this paper, we propose a family of label recovery problems on weighted Euclidean random graphs. The vertices of a graph are embedded in R^d according to a Poisson point process and are assigned to a discrete community label. Our goal is to infer the vertex labels, given edge weights whose distributions depend on the...
We consider range minimization problems featuring exponentially many variables, as frequently arising in fairness-oriented or bi-objective optimization. While branch and price is successful at solving cost-oriented problems with many...
