Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

The issue of harnessing machine learning (ML) algorithms for the prediction of adverse
medical events is important considering the prevalence of vast repositories of patient-level …

Recently, modeling of decision making and control systems that include heterogeneous
smart sensing devices (machines) as well as human agents as participants is becoming an …

While there has been extensive work on modeling of human decision-making both for
individuals and groups from a cognitive psychology point of view, research on this topic from …

In critical environments that require a high accuracy of decisions, utilizing human cognitive
strengths and expertise in addition to machine observations is advantageous to improve …

This paper establishes a mathematical framework to analyze the behavioral utility-based
distributed detection problem for 𝑀-ary hypothesis testing with conditionally independent …

In this paper, the aim is to model the dependence between a continuous machine
observation and a discrete human decision maker using copula theory for a binary …

Unlike decision making systems made up of physical sensors where the system parameters
are known a priori and can be controlled at will, human behavior in decision making is …

We analyze the asymptotic performance of likelihood ratio based collaborative human-
machine decision making systems. Human agents are assumed to make threshold based …

This work considers a Bayesian signal processing problem where increasing the power of
the probing signal may cause risks or undesired consequences. We employ a market based …