Malik Majette is researching data-driven simulations of virtual social environments under the advisorship of Dr. Stephen Guy at North Carolina State University. Specifically, Majette aims to use virtual reality, facial animations, and architectural evaluation to recreate gatherings in the ancient Pnyx structure in Athens through intelligent virtual humans. By basing agent behaviors on universal laws of pedestrian movement and incorporating realistic facial expressions collected from medical studies, Majette's model can simulate large crowds naturally interacting in the deteriorated structure and reproduce genuine human emotions to provide an immersive experience of ancient democratic assemblies.

1. Malik Majette
Data-driven Simulation and Evaluation of Virtual Social Environments
Advisor: Dr. Stephen Guy
Home Institution: North Carolina State University
Abstract: Modeling virtual humans in settings to intelligently interact and instinctively gesture is
an active research area with broad applications. In our research we focus on the combination of
virtual reality, facial animations, and architectural evaluation to present a realistic immersion in
ancient structures that have deteriorated, and no longer support the initial magnitude of
occupancy. Specifically, the Pnyx, an ancient Athens structure said to be the birthplace of
democratic assemblies, is currently unable to actualize these archaic events to tourists due to its
decay. We developed a virtual program to represent gatherings in the Pnyx that naturally
condense towards a speaker’s podium and make a variety of facial expressions in response to
each other. Constructing this model presented a computational challenge in large simulations
since the authenticity of human emotion is difficult to invoke in graphical simulations, and there
is no previous data of how the Athenians organized or to support the claim that the structure had
capacity for 16,000 men. We address these issues using a data-driven approach to simulate
intelligent agents in the Pnyx based on the concept of a universal power law governing
pedestrian behavior. In our model large crowds can enter into the structure while conforming to
natural behaviors such as avoiding collisions, natural dispersion, and social space. Furthermore,
in collaboration with doctors from the UMN Otolaryngology Department we collect and evaluate
facial features across a large sample, which is utilized to reproduce genuine emotions in virtual
agents. With real-world pedestrian interactions and data-driven facial animations our model
provides a convincing and accurate representation of democratic assemblies from the beginning
of human recording.