Empirical Systems & Pedagogy

Active Research Domains

Our methodology investigates scalable architectures and modern pedagogical frameworks to bridge technical complexity with classroom execution, establishing robust environments for student-centric computer science education.

Scalable Computational Models

Pedagogical Systems Engineering

Developing distributed systems architectures that support real-time data processing while maintaining strict performance guarantees in resource-constrained environments.

Designing and evaluating empirical frameworks for computer science curricula, focusing on student-centric learning outcomes and automated feedback systems.

Peer-Reviewed Publications

Automated Feedback in Systems Curricula

An empirical study on the impact of automated testing pipelines on student learning outcomes in undergraduate systems programming courses.

Scalable Architectures for Distributed Learning

This paper presents a lightweight, containerized infrastructure designed to scale computational resources dynamically during large-scale coding assessments.

Empirical Methods in Software Pedagogy

A longitudinal analysis of student-centric curriculum design, demonstrating measurable improvements in retention and technical competency across diverse cohorts.

Academic Collaboration

I am actively seeking opportunities for research collaborations, peer reviews, and graduate student advising in computer science education and systems engineering.