2026 Colloquium
AI Technology Applications for Public Safety
CINSER Annual Colloquium 2026
Thursday, October 15, 2026
9am to 1pm CST
This is a free online event that is open to the public. Registration is required.
Register
AI Technology Applications for Public Safety
is organized in collaboration with the IEEE Public Safety Technology (PST) Initiative,
the Texas A & M Institute of Data Science and the Center for Information Security
Education and Research (CINSER).
This colloquium will explore the diverse and rapidly expanding applications of artificial
intelligence in public safety. AI technologies are being applied across a broad range
of domains, including emergency management, disaster response, transportation safety,
cybersecurity, public health, and critical infrastructure protection. Through presentations
by distinguished speakers and an interactive panel discussion, attendees will gain
insights into emerging technologies, real-world applications, implementation challenges,
and ethical considerations. The event aims to promote knowledge sharing and dialogue
on the opportunities and challenges of leveraging AI to enhance public safety, resilience,
and community well-being.
Featured Speakers:
- Kathy Grise, IEEE Public Safety Technology (PST) Initiative
- Jian Tao, Texas A&M University
- Hany Elgala, University at Albany, SUNY
- Scott Ledgerwood, National Institute of Standards and Technology (NIST)
Advancing AI-Enabled Public Safety Training and Communications with a Digital Twin-based
Testbed
Dr. Jian Tao, Texas A&M University
Assistant Professor, Visual Computing and Computational Media Section
Assistant Director for Project Development, Texas A&M Institute of Data Science
Director, Digital Twin Lab, Texas A&M Institute of Data Science
Summary
This talk presents the development of a Digital Twin-based testbed for public safety
training & communications: a dynamic, data-driven virtual environment designed to
support the testing, evaluation, and training of next-generation public-safety technologies.
By bringing together realistic 3D environments, communication systems, sensor and
IoT data, simulation, AI, and visualization, the platform provides a safe, repeatable
setting for exploring how first responders can operate more effectively in complex
emergency scenarios. The presentation will discuss the system’s vision, technical
architecture, and potential uses—from assessing public-safety communications and situational-awareness
tools to supporting responder training and AI-assisted decision-making. It will also
highlight the value of connecting physical and virtual environments to enable more
resilient, interoperable, and human-centered emergency-response technologies. This
work builds on the Digital Twin Lab’s public-safety research, including a NIST-supported
digital-twin-enabled testbed for public-safety communication technologies.
From Prediction to Response: The Emerging Role of AI in Emergency Services
Scott Ledgerwood, NIST
User Experience/Location-Based Services Portfolio Lead, NIST
Summary
AI tools are entering public safety operations from risk prediction and early detection
to active response and post-incident analysis. This talk reviews current deployments
and research, highlights how recent frontier models are extending these capabilities,
and examines the cybersecurity and reliability concerns that make guardrails and human
oversight essential in life-safety systems.
From Sensing to Decision: Building Trustworthy AI-Enabled Systems for Public Safety
Dr. Hany Elgala, University at Albany, SUNY
Associate Professor of Electrical and Computer Engineering
Associate Director of the AI & Society College
Summary
Advances in artificial intelligence, embedded sensing, edge computing, and wireless
communications are creating new opportunities to enhance public safety through more
timely and informed decision-making. This talk will explore a systems-level view of
this emerging landscape, following the pathway from sensing and connectivity to AI-enabled
situational awareness and human decision support. Drawing on real-world research pilots
and emerging applications, examples will include intelligent sensor networks, edge-AI,
and unmanned aerial systems. The talk will also examine where intelligence should
reside, on the device, at the edge, or in the cloud. Finally, it will consider privacy,
human-oversight, and governance requirements needed to build trustworthy AI-enabled
public-safety systems for society.
Register
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