Informatics and Computer Engineering Education
I develop research-oriented software systems across AI in education, learning analytics, computer vision, Moodle/LMS development, and applied ICT products for education and health contexts.
Fit for PMDSU promoter discussion through research themes, publications, and implemented systems.
Exploring LMS behavioral traces, student modeling, dashboard analytics, and evidence-oriented interventions for intelligent learning environments.
Designing feedback mechanisms, gamified learning interactions, and Moodle-based features that support motivation and engagement.
Applying pose estimation, face recognition, and movement analysis to build assistive, educational, and monitoring systems.
Building prototypes, plugins, dashboards, APIs, and full-stack systems that turn research ideas into usable technical artifacts.
These directions show the next academic path: not only what I have built, but how the systems can become research problems, methods, and contributions.
Designing adaptive feedback mechanisms in Moodle or similar LMS environments using learner activity traces, engagement signals, and learning progress indicators.
Expected contribution
A research-ready LMS feature that can support experimentation on student engagement, motivation, and learning intervention timing.
Modeling student state from behavioral traces such as activity access, submission patterns, quiz attempts, leaderboard behavior, and attendance signals.
Expected contribution
An interpretable analytics framework that helps educators identify engagement patterns and intervention opportunities without overclaiming prediction accuracy.
Exploring pose detection and face recognition as supportive signals for interaction, accessibility, attendance, posture analysis, or therapy-oriented learning contexts.
Expected contribution
A responsible applied-computing direction that connects computer vision prototypes with education, health, and human-centered system design.
Skills are organized by academic relevance instead of presented as a long unstructured tool list.
Methods used to structure academic inquiry and evaluation.
Applied AI skills for education, vision, and analytics systems.
Tools and frameworks for turning research ideas into systems.
Skills for communicating research products clearly.