Ongoing research

Neuroadaptive extended reality for clinical training

Investigating real-time biosensor-driven adaptation of VR training scenarios across clinical education, spanning emergency medicine, pediatric readiness, and surgical training. The goal is to adjust training difficulty and content based on a learner’s physiological state as they progress through a scenario.

Surgical digital twins for infection prevention

Combining agent-based modeling and multi-agent reinforcement learning to evaluate infection-prevention policies in surgical settings, building toward a digital twin that can test policy interventions computationally before deployment in clinical workflows.

Active

Redesigning Emergency Department Clinician Shift Scheduling to Improve Well-being and Patient Outcomes (EDSHIFT)

NIOSH / CDC · Co-Investigator · Oct 2024 – Sep 2026

NIH RePORTER: Project record

A mixed-methods framework for redesigning ED nurse and physician shift schedules that integrates clinician preferences and physiological well-being indicators, including burnout, fatigue, and cortisol markers, alongside operational and patient-safety data. The team analyzes current staffing schedules and clinician-reported preferences, then feeds those relationships into a modeling framework, in collaboration with Clemson University, that generates functional shift schedules benchmarked against a computer-based simulation model of the partner hospital’s ED.

Clinician burnout and chronic stress in Emergency Departments carry real costs for clinician health, patient safety, and care quality, yet most shift-scheduling research focuses on identifying burnout’s causes rather than designing system-level interventions to prevent it. EDSHIFT addresses that gap with mathematical modeling that treats clinician well-being as a first-class scheduling constraint alongside patient flow and safety, aiming to reduce workflow imbalance and stress at the planning stage itself.

Improving patient experience and access to care

Stanford Health Care · Principal Investigator · 2022 – Ongoing

Applying data analytics, operations research, and simulation methods to improve patient access and experience across Stanford Health Care’s contact center and clinical network. The project spans both contact center operations and broader access-to-care challenges across Stanford’s clinical network.

AI, Robotics, and Industry 5.0 Summer Camp & AI, Robotics, and Entrepreneurship (AIRE) Summer Institute

National Science Foundation & VentureWell · Co-Principal Investigator · Apr 2026 – Mar 2027

NSF Award Number: 2611147

Hands-on summer programs preparing high school students for AI-enhanced service careers through robotics and entrepreneurial thinking, run through UCF’s AIRE Summer Institute and Summer Camp at NeoCity Academy. Students work in small teams across a range of platforms, including Sphero BOLT+, Lego robotics, robot dogs, drones, Raspberry Pi, and VEX, applying a four-pillar AI competency framework (awareness, interaction, application, and human-AI co-creation) to learn AI and robotics fundamentals, systems design, and entrepreneurial thinking, and culminating in a mock business plan and a UCF completion certificate.

Evidence-based models for teaching AI and robotics to high school students, especially ones that pair technical skill-building with entrepreneurship and ethical reasoning, remain scarce. The project addresses that gap and advances the national interest in a human-centered AI workforce by expanding access to advanced technology education for students from service-industry communities, while producing open-access instructional materials, professional learning resources for educators, and empirical evidence on integrating AI, robotics, and entrepreneurship education into K-12 STEM learning nationwide.

Space Habitat Hospitality: a VR-biosensing framework for crew interaction, environment design, and guest well-being

Rosen College of Hospitality Management · Co-Principal Investigator · Jan 2026 – Sep 2026

Developing an integrated VR-biosensing research framework examining how space-habitat design and crew-guest interactions shape psychological, emotional, and physiological well-being during simulated orbital stays, in collaboration with PI Dr. Arthur Huang. The study uses a multi-user VR platform with paired “crew” and “guest” roles alongside HRV, EDA, and pupillometry measures to build a foundational theoretical model of space habitat hospitality, informing next-generation habitat design and crew training protocols for commercial spaceflight.

CyberAI Innovation: Training the Human Firewall Through Generative AI Adversaries and Metacognitive Scaffolding for Cybersecurity Workforce Resilience

National Science Foundation (CyberAICorps SFS) · Principal Investigator · Aug 2026 – Jul 2029

NSF Award Number: 2623070

A multi-agent adaptive intelligent tutoring system that trains cybersecurity professionals to recognize and resist AI-enabled threats, including AI-generated social engineering, prompt injection in AI-assisted workflows, and insider behavioral anomalies. An Adversary Agent generates adaptive, profile-targeted threat scenarios, a Diagnostic Agent classifies individual metacognitive miscalibration profiles from learner decision and confidence data, and a Metacognitive Scaffolding Agent delivers personalized calibration interventions matched to each learner’s profile. The three-year mixed-methods evaluation will serve 120 to 200 graduate learners at UCF, a National Center of Academic Excellence in Cybersecurity, with a pilot at a partner institution coordinated through the Florida High Tech Corridor.

The project addresses a documented gap between the sophistication of AI-driven cyberattacks and the cognitive readiness of the professionals defending against them, closing a metacognitive miscalibration gap left unaddressed by conventional cybersecurity training. Funded through NSF’s CyberAICorps Scholarship for Service (SFS) Innovation Track, it will release all training modules, scenario libraries, calibration instruments, and system source code as open educational resources, strengthening national capacity to educate and retain AI and cybersecurity workforce talent.

Completed

Epic Games MegaGrant-supported XR research

Epic Games · 2020 – 2021

Developed an HRV biofeedback game in Unreal Engine, supporting immersive VR interventions for clinical pain and anxiety management.

Various XR + biofeedback projects (pain, anxiety, and substance use)

UNC Charlotte

A series of internally and seed-funded projects exploring XR and biofeedback interventions for pain, anxiety, and substance use, supported by the UNCC SDS Seed Grant (Co-Principal Investigator, 2023–2024), UNCC Faculty Research Grant (Principal Investigator, 2023–2024), UNCC ArtXSci Award (Principal Investigator, 2022–2024), and UNCC College of Engineering Seed Grant (Principal Investigator, 2023).

SBIR Phase I: An AI-inspired computing application for detecting the early onset of pneumonia (COVID-19)

National Science Foundation · Co-Founder · 2021 – 2022

Developed a human-AI computing application for early detection of pneumonia, a common COVID-19 complication, using remote physiological and symptomatic monitoring streamed to a cloud-based predictive analytics engine. The system’s adaptive classifier expanded model dimensionality in real time by interactively requesting patient symptom input as needed, alerting healthcare providers when a pneumonia-onset pattern was detected.

Redesigning Emergency Department Clinician Shift Scheduling to Improve Well-being and Patient Outcomes (EDSHIFT)

NIOSH / CDC · Co-Investigator · Oct 2024 – Sep 2026

NIH RePORTER: Project record

A mixed-methods framework for redesigning ED nurse and physician shift schedules that integrates clinician preferences and physiological well-being indicators, including burnout, fatigue, and cortisol markers, alongside operational and patient-safety data. The team analyzes current staffing schedules and clinician-reported preferences, then feeds those relationships into a modeling framework, in collaboration with Clemson University, that generates functional shift schedules benchmarked against a computer-based simulation model of the partner hospital’s ED.

Clinician burnout and chronic stress in Emergency Departments carry real costs for clinician health, patient safety, and care quality, yet most shift-scheduling research focuses on identifying burnout’s causes rather than designing system-level interventions to prevent it. EDSHIFT addresses that gap with mathematical modeling that treats clinician well-being as a first-class scheduling constraint alongside patient flow and safety, aiming to reduce workflow imbalance and stress at the planning stage itself.

Improving patient experience and access to care

Stanford Health Care · Principal Investigator · 2022 – Ongoing

Applying data analytics, operations research, and simulation methods to improve patient access and experience across Stanford Health Care’s contact center and clinical network. The project spans both contact center operations and broader access-to-care challenges across Stanford’s clinical network.

AI, Robotics, and Industry 5.0 Summer Camp & AI, Robotics, and Entrepreneurship (AIRE) Summer Institute

National Science Foundation & VentureWell · Co-Principal Investigator · Apr 2026 – Mar 2027

NSF Award Number: 2611147

Hands-on summer programs preparing high school students for AI-enhanced service careers through robotics and entrepreneurial thinking, run through UCF’s AIRE Summer Institute and Summer Camp at NeoCity Academy. Students work in small teams across a range of platforms, including Sphero BOLT+, Lego robotics, robot dogs, drones, Raspberry Pi, and VEX, applying a four-pillar AI competency framework (awareness, interaction, application, and human-AI co-creation) to learn AI and robotics fundamentals, systems design, and entrepreneurial thinking, and culminating in a mock business plan and a UCF completion certificate.

Evidence-based models for teaching AI and robotics to high school students, especially ones that pair technical skill-building with entrepreneurship and ethical reasoning, remain scarce. The project addresses that gap and advances the national interest in a human-centered AI workforce by expanding access to advanced technology education for students from service-industry communities, while producing open-access instructional materials, professional learning resources for educators, and empirical evidence on integrating AI, robotics, and entrepreneurship education into K-12 STEM learning nationwide.

Space Habitat Hospitality: a VR-biosensing framework for crew interaction, environment design, and guest well-being

Rosen College of Hospitality Management · Co-Principal Investigator · Jan 2026 – Sep 2026

Developing an integrated VR-biosensing research framework examining how space-habitat design and crew-guest interactions shape psychological, emotional, and physiological well-being during simulated orbital stays, in collaboration with PI Dr. Arthur Huang. The study uses a multi-user VR platform with paired “crew” and “guest” roles alongside HRV, EDA, and pupillometry measures to build a foundational theoretical model of space habitat hospitality, informing next-generation habitat design and crew training protocols for commercial spaceflight.

CyberAI Innovation: Training the Human Firewall Through Generative AI Adversaries and Metacognitive Scaffolding for Cybersecurity Workforce Resilience

National Science Foundation (CyberAICorps SFS) · Principal Investigator · Aug 2026 – Jul 2029

NSF Award Number: 2623070

A multi-agent adaptive intelligent tutoring system that trains cybersecurity professionals to recognize and resist AI-enabled threats, including AI-generated social engineering, prompt injection in AI-assisted workflows, and insider behavioral anomalies. An Adversary Agent generates adaptive, profile-targeted threat scenarios, a Diagnostic Agent classifies individual metacognitive miscalibration profiles from learner decision and confidence data, and a Metacognitive Scaffolding Agent delivers personalized calibration interventions matched to each learner’s profile. The three-year mixed-methods evaluation will serve 120 to 200 graduate learners at UCF, a National Center of Academic Excellence in Cybersecurity, with a pilot at a partner institution coordinated through the Florida High Tech Corridor.

The project addresses a documented gap between the sophistication of AI-driven cyberattacks and the cognitive readiness of the professionals defending against them, closing a metacognitive miscalibration gap left unaddressed by conventional cybersecurity training. Funded through NSF’s CyberAICorps Scholarship for Service (SFS) Innovation Track, it will release all training modules, scenario libraries, calibration instruments, and system source code as open educational resources, strengthening national capacity to educate and retain AI and cybersecurity workforce talent.

Epic Games MegaGrant-supported XR research

Epic Games · 2020 – 2021

Developed an HRV biofeedback game in Unreal Engine, supporting immersive VR interventions for clinical pain and anxiety management.

Various XR + biofeedback projects (pain, anxiety, and substance use)

UNC Charlotte

A series of internally and seed-funded projects exploring XR and biofeedback interventions for pain, anxiety, and substance use, supported by the UNCC SDS Seed Grant (Co-Principal Investigator, 2023–2024), UNCC Faculty Research Grant (Principal Investigator, 2023–2024), UNCC ArtXSci Award (Principal Investigator, 2022–2024), and UNCC College of Engineering Seed Grant (Principal Investigator, 2023).

SBIR Phase I: An AI-inspired computing application for detecting the early onset of pneumonia (COVID-19)

National Science Foundation · Co-Founder · 2021 – 2022

Developed a human-AI computing application for early detection of pneumonia, a common COVID-19 complication, using remote physiological and symptomatic monitoring streamed to a cloud-based predictive analytics engine. The system’s adaptive classifier expanded model dimensionality in real time by interactively requesting patient symptom input as needed, alerting healthcare providers when a pneumonia-onset pattern was detected.

Neuroadaptive extended reality for clinical training

Investigating real-time biosensor-driven adaptation of VR training scenarios across clinical education, spanning emergency medicine, pediatric readiness, and surgical training. The goal is to adjust training difficulty and content based on a learner’s physiological state as they progress through a scenario.

Surgical digital twins for infection prevention

Combining agent-based modeling and multi-agent reinforcement learning to evaluate infection-prevention policies in surgical settings, building toward a digital twin that can test policy interventions computationally before deployment in clinical workflows.