What I do and why it matters.

"I build protective design systems for people inside institutions not designed with their full humanity in mind."

My work begins with a structural observation: the systems that govern education, technology, and workplace safety are often well-intentioned but poorly calibrated for the humans who actually move through them. I work at the intersection of human factors, AI ethics, educational psychology, and instructional design — not because the disciplines overlap conveniently, but because the problems I am drawn to require all of them at once.

I am a framework thinker and a practitioner. I do not describe problems and stop there. I build tools — frameworks, rubrics, deployed AI agents, curriculum architectures — that can be used in real classrooms by real educators with real students. Everything I develop is classroom-tested before it becomes scholarship, and grounded in validated theory before it becomes practice.

Over three years of largely independent work, I developed a seven-layer framework ecosystem for ethical AI integration in higher education — without a research mentor, while completing a PhD and starting a new faculty position. That context matters not as biography, but as evidence of what this kind of work requires and what it produces.

Three streams of inquiry.

My research does not fit neatly into one department or one conversation. It spans three distinct streams, each rigorous in its own right, each connected to the others by a common commitment to designing for people as they actually are.

1

AI-Integrated Education

Building human-centered frameworks for ethical, pedagogically sound AI integration in higher education. This is my most developed stream — a seven-layer ecosystem addressing ethics, literacy, interaction design, agent design, output quality, evaluation, and critical thinking protection. All frameworks are classroom-tested, published or in active submission, and grounded in human factors and educational psychology.

2

Ergonomics & Human Factors

Using machine learning and computer vision to classify hand movements in repetitive motion tasks — specifically to model how fatigue develops over time. This is my PhD dissertation work at Western Michigan University. It is methodologically sophisticated, interdisciplinary, and addresses a gap in how occupational fatigue is currently measured and understood.

3

Trauma-Informed Pedagogy

Designing learning environments that recognize the full humanity of students and educators. Grounded in care ethics, grief scholarship, and direct practice. This stream includes published work on trauma-informed and student-centered pedagogy, policy recommendations for supporting women scholars navigating grief in academia, and the development of instructional tools that prioritize psychological safety alongside academic rigor.

Background and positions.

Current role Assistant Teaching Professor, College of Engineering and Innovation · Bowling Green State University
PhD Interdisciplinary PhD in Engineering — Ergonomics, Machine Learning, Computer Vision (ABD) · Western Michigan University
Previous role AI Graduate Fellow, WMUx · Western Michigan University (2024–2025)
Master's MS Project Management · Keller Graduate School of Management
Undergraduate BS Mechanical Engineering · Ain Shams University, Cairo, Egypt
Certification Associate Ergonomics Professional (AEP) · Board of Certification in Professional Ergonomics
Award All University Graduate Teaching Effectiveness Award · Western Michigan University, 2024–2025
Fellowship Active Learning Certificate Program · Center for Faculty Excellence, BGSU (2025)

Student-centered. Trauma-informed. AI-integrated with intention.

My teaching philosophy is not a statement — it is a set of design decisions visible in every course I build. I model the behaviors I expect from students: I cite my own AI use in course materials, I disclose my design process, and I treat the classroom as a space where thinking happens rather than where conclusions are delivered.

Student-centered design

Learning objectives drive every decision — not content coverage, not convenience. Students are the designers of their own understanding.

Trauma-informed practice

Students arrive with full lives. Course design that ignores this produces worse learning and worse people. I design for the whole person.

Ethical AI integration

AI belongs in the classroom — with clear policy, modeled use, and structures that protect rather than replace student thinking.

Transparency as pedagogy

I make my own process visible to students. How I think, how I use tools, how I revise — these are instructional materials, not private practice.