Research

Current Grants

• The AI Voyage: Integrating AI Literacy into Computer Science Curricula with Accessible Hands-On Learning Activities. (NSF-IUSE, PI)

• Fire and ICE: Raising Security Awareness through Experiential Learning Activities for Building Trustworthy Deep Learning-based Applications. (NSF-SaTC, PI)

Past Grants

• Advancing Cybersecurity Learning through Inquiry-based Laboratories on a Container-based Virtualization Platform. (NSF-SaTC, PI)

• Enhancing Mobile Security Education by Creating Eureka Experiences. (NSF-CyberTraining, PI)

• A Social and Context Aware Spectrum Management Framework for Heterogeneous Cognitive Radio Networks. (NSF-CNS, PI)

Publications

You can find my publications through my Google Scholar profile or ORCID.

Eureka Labs for Cybersecurity Education

We have developed a number of hands-on labs for better understanding cybersecurity and artificial intelligence (AI) concepts and technologies, which is available at Eureka Labs.

AI-related Projects

In an era where AI transcends mere buzzword status to become a catalyst for innovation, we—a collective of engaged researchers and educators—aspire to establish an AI Institute for Interdisciplinary Education and Research. A compilation of current research initiatives and projects can be found here.

• ClassifAI: This is an online video/audio analysis platform that is geared towards assisting the teachers and faculty of educational institutions in analyzing and understanding how their interaction with students translates into real learning. Our platform is meant to replace the current, manual method of analysis that many teachers/instructors perform to try and quantify different metrics about their teacher-student interaction. Instructors have expressed desire to view metrics such as the time the teacher talks during a lesson, what is the response time of students to those questions, and other data points such as the types of questions being asked. Quantifying these instructional variables helps these instructors more accurately understand the areas that they are strong in, and more importantly, the areas in which they can be more interactive with the students as to allow them to better absorb the lessons being taught. With the help of our platform (hosted at https://classifai.tcu.edu), we can allow teachers to quickly and efficiently gather this data about each of their lessons so that data driven changes in teaching techniques is possible, and moreover, so that teachers can identify potential vectors of ineffective instruction.

• HealthLitIQ: Parents with low health literacy may struggle to understand health information. Nurses are well- positioned to adopt health literacy practices which have been shown to improve child outcomes. When translating evidence into practice, fidelity to health literacy practices such as using plain language, limiting information to 3-5 key topics, and using teach back is important to realize outcomes seen in controlled studies. Despite health literacy training efforts, adoption of health literacy practices has been challenging. Audit and feedback is an evidence based implementation strategy that has been shown to change clinician behavior but is a human resource intensive strategy. The emergence of artificial intelligence tools has improved efficiency and may expedite audit and feedback processes. This project hopes to develop and and validate of an AI-based audit and feedback tool tailored specifically to address the fidelity of health literacy practices.

• From Growing Pains to Growth: This project aims to develop and test an AI-powered intervention on substance use and related behavioral issues for youth in transition. The intervention will focus on two important types of psychosocial functioning underlying substance use in daily life: social communication and emotion regulation, and integrate two components: an AI-delivered personalized intervention and AI-powered in vivo assessment on intra-personal and ecological factors.