Research
My research focuses on curriculum learning methodologies and AI-powered educational technology, with particular emphasis on accessibility for students with learning difficulties. My work combines computational approaches with real-world implementation, ensuring theoretical advances translate into practical solutions that genuinely serve learners.
Current Projects
Curriculum Learning for Image Classification CNNs
Status: completed | Date: 8/15/2024
Undergraduate research investigating curriculum learning approaches for image classification CNNs, presented at IBM Thomas J. Watson Laboratory (AICS'24). Explored complexity-based training methods with focus on experimental methodology.
Collaborators: ULL DADL Lab - Dr. Aminul Islam
AI-Powered Educational Technology Development
Status: ongoing | Date: 6/15/2024
Development of AI-powered accessibility systems for educational technology, focusing on students with learning difficulties. Includes work with London-based EdTech startup and award-winning accessibility applications.
Collaborators: BeNakama (London), Aluminotes Team
Research Philosophy
I believe that computer science research should address pressing social challenges, particularly in education. My work is motivated by the educational disparities I've witnessed and experienced firsthand - from the failures of systems like Edgenuity to the transformative potential of well-designed educational technology.
My approach centers students with learning difficulties as primary users, applying an "anti-Edgenuity" design philosophy where every decision prioritizes genuine learning over administrative convenience. Each project combines rigorous computational methods with accessibility-first design, ensuring solutions that benefit all learners.