This paper reports a case study of an application of high-resolution agent-based modeling and simulation to pandemic response planning on a university campus. In the summer of 2020, we were tasked with a COVID-19 pandemic response project to create a detailed behavioral simulation model of the entire campus population at Binghamton University. We conceptualized this problem as an agent migration process on a multilayer transportation network, in which each layer represented a different transportation mode. As no direct data were available about people's behaviors on campus, we collected as much indirect information as possible to inform the agents' behavioral rules. Each agent was assumed to move along the shortest path between two locations within each transportation layer and switch layers at a parking lot or a bus stop, along with several other behavioral assumptions. Using this model, we conducted simulations of the whole campus population behaviors on a typical weekday, involving more than 25,000 agents. We measured the frequency of close social contacts at each spatial location and identified several busy locations and corridors on campus that needed substantial behavioral intervention. Moreover, systematic simulations with varying population density revealed that the effect of population density reduction was nonlinear, and that reducing the population density to 40-45% would be optimal and sufficient to suppress disease spreading on campus. These results were reported to the university administration and utilized in the pandemic response planning, which led to successful outcomes.

We have developed an AI-powered socio-technical system for making online learning in higher education more accessible, affordable and achievable. In particular, we have developed four novel and intertwined AI technologies: (1) VERA, a virtual experimentation research assistant for supporting inquiry-based learning of scientific knowledge, (2) Jill Watson Q&A, a virtual teaching assistant for answering questions based on educational documents including the VERA user reference guide, (3) Jill Watson SA, a virtual social agent that promotes online interactions, and (4) Agent Smith, that helps generate a Jill Watson Q&A agent for new documents such as class syllabi. The results are positive: (i) VERA enhances ecological knowledge and is freely available online; (ii) Jill Watson Q&A has been used by >4,000 students in >12 online classes and saved teachers >500 hours of work; (iii) Jill Q&A and Jill Watson SA promote learner engagement, interaction, and community; and (iv). Agent Smith helps generate Jill Watson Q&A for a new syllabus within ~25 hours. Put together, these innovative technologies help make online learning simultaneously more accessible (by making materials available online), affordable (by saving teacher time), and achievable (by providing learning assistance and fostering student engagement).

Stamford, Conn., recently revealed five distinct emerging technology trends that create and enable new experience. The first is sensing and mobility, which combines sensor technologies with AI to enable businesses to gain a better understanding of the world around them. One example is leveraging AR (augmented reality) cloud to create a 3D map of the world. The second is the augmented human, which enables creation of cognitive and physical improvements as an integral part of the human body. An example of this is the ability to provide superhuman capabilities such as creation of limb with prosthetics.

The ONUG narrative is focused on digital transformation within the Global 2000 and its underpinning technologies plus IT culture, organization and skills realignment to manage this exciting transition. Technologies, such as hybrid multi-cloud, a secure internet, machine learning, artificial intelligence, automated and software-driven infrastructure, software-defined Wide Area Networking 2.0, are all but some of the topics on the agenda at ONUG Fall 2019. Front and center at ONUG Fall will be reference solutions to the most common digital transformation problems. These reference solutions are software building blocks that construct a hybrid and/or multi-cloud infrastructure that connects, secures, monitors and orchestrates workloads between on- and off-premises.