AI-Based Spatial Computing with BIM: Performance, Sustainability, and Wayfinding on the UC Campus
This project introduces an AI-enhanced spatial computing framework that integrates building-scale digital twins with intelligent autonomous navigation. Using BIM-derived geometry and utility metadata, the system combines LLM-assisted building-performance analytics with predictive modeling to support sustainable operations across an interactive, campus-scale digital twin environment. In parallel, we present INARA, a ROS 2–based indoor navigation platform that merges BIM-accurate simulation environments with a hybrid deep-reinforcement-learning and classical-control architecture, enabling safe, adaptive mobile-robot navigation within UC facilities.
Together, these systems advance AI-driven spatial computing by unifying building analytics, embodied intelligence, and digital–physical interoperability—laying the foundation for next-generation smart-building management and autonomous robotic applications.
https://i0.wp.com/ming3d.com/new/wp-content/uploads/2026/01/bearcat_AI_award.jpg?fit=898%2C546546898Ming Tanghttp://ming3d.com/new/wp-content/uploads/2022/01/TY_logo-300x300-new.pngMing Tang2026-01-26 15:59:432026-03-31 19:39:56AI symposium, Bearcat AI Award
Technology forHealth, Resilience, Equity , and Decision-Making
Team: A&S: Kelly Merrill, Lauren Forbes, Briana Simms, Paris Wheeler, Diego Cuadros, DAAP: Ming Tang
Funding: Center for Clinical & Translational Science & Training. CCTST. Pilot Grant. $50,000. PI. Merrill, Forbes, Co-I. Tang, Cuadros, Simms, Wheeler. 2026. University of Cincinnati.
Project Aims:
Aim 1: Co-design a set of digital data governance policies that reflect Black community preferences, concerns, and expectations around the use of their digital health data.
Aim 2: Assess the utility of digital twin technology (3D city modeling with VR) for community advocacy and population health-related objectives.
Aim 3: Co-design and develop a community-driven, population health intervention and participatory planning tool.
Ming Tang’s involvement in the human-centered digital twin can be traced back to his work at the MSU MIND Lab roughly two decades ago, and the THRED project builds directly on that foundation. There is also a clear conceptual link to HomeNetToo project then, where multiple interfaces—a standard web interface, a spatial interface, and an interpersonal interface—were developed to examine how different modes of interaction influence knowledge acquisition across varying cognitive styles. That early work established an important premise: the design of an interface fundamentally shapes how users interpret, understand, and engage with information.
THRED extends this line of inquiry beyond controlled experimental settings into a real-world, system-scale platform by integrating digital twins, and data-driven decision environments. Rather than comparing interfaces in isolation, it synthesizes them—bringing together spatial (3D environments), informational (data visualization and dashboards), and social (community and stakeholder engagement) interfaces into a unified ecosystem. In this sense, THRED represents a shift from experimental interaction design toward an applied, human-centered digital twin framework. It maintains continuity with earlier immersive technology research while significantly expanding its scope, enabling new forms of collective understanding, decision-making, and behavioral insight at urban and societal scales.
Adondale Digtal Twin (ADT) Prototypes
1. DATA VIZ ADT
mobile phone must be put in horizonal orientation in order to see buttons
We are excited to announce the launch of Phase 3 of the VR-Based Employee Safety Training: Therapeutic Crisis Intervention Simulation project, building on the success of the previous two phases. This interdisciplinary collaboration brings together the Immersive Learning Lab and the Employee Safety Learning Lab at Cincinnati Children’s Hospital Medical Center (CCHMC), in partnership with the Extended Reality Lab (XR-Lab) at the University of Cincinnati.
This phase will focus on developing an advanced virtual hospital environment populated with digital patients to simulate a variety of real-world Therapeutic Crisis Intervention (TCI) scenarios. The digital twins encompass both the hospital setting and patient avatars. The project aims to design immersive training modules, capture user performance data, and conduct a rigorous evaluation of the effectiveness of VR-based training in enhancing employee safety and crisis response capabilities
Principal Investigator: Ming Tang. Funding Amount: $38,422. Project Period: April 1, 2025 – December 1, 2026
CCHMC Collaborators: Dr. Nancy Daraiseh, Dr. Maurizio Macaluso, Dr. Aaron Vaughn.
Research Domains: Virtual Reality, Safety Training, Therapeutic Crisis Intervention, Mental Health, Digital Twins, Digital Humans, Human Behavior Simulation.
We look forward to continuing this impactful work and advancing the role of immersive technologies in healthcare education and safety training
Concept of Digital Twin: Digital Patient + Digital Hospital.
https://i2.wp.com/ming3d.com/new/wp-content/uploads/2025/03/image.png?fit=1366%2C100910091366Ming Tanghttp://ming3d.com/new/wp-content/uploads/2022/01/TY_logo-300x300-new.pngMing Tang2025-03-18 17:48:022026-06-01 19:38:44SMAT: Scalable Multi-Agent AI for DT
Project VISM (Virtual Interactive Simulation for Material customization)
Interactive Visualization with User-Controlled, Procedural-Based, and Physical-Based Material Customization.
PI. Ming Tang.
P&G Team: Kim Jackson, Andrew Fite, Fei Wang, Allison Roman