I build systems, not demos — favoring an understanding of what's under the abstraction
(memory, protocols, gradients) over relying on frameworks I can't explain.
Languages
Backend
Client
Applied AI
Full-stack ride-sharing system built for real production patterns, not a tutorial clone:
- Backend: ASP.NET Core Web API (.NET 10) with layered architecture — Repository, Service, and Controller layers, custom exceptions, and a
GlobalExceptionHandler - Auth: BCrypt password hashing + JWT with refresh token rotation and reuse detection.
- Clients: Native SwiftUI apps for both Passenger and Driver roles.
- AI engine: Separate Python service for pricing/routing intelligence.
Currently finishing FluentValidation across the API before moving to the next stage.
Cross-platform file sync tool — Flutter client, ASP.NET Core backend, JWT auth, Cloudflare R2 object storage, with file versioning and shareable access control.
- Computer Architecture project — low-level hardware/software system work; used by a BIIT instructor as teaching material in the Computer Architecture course.
- IPFS File-Sharing Prototype — decentralized storage using content-addressed chunks and P2P validation; used by a BIIT instructor as teaching material in the Information Security / Cyber Security course.
- Society Management System — WinForms + SQL Server.
- Assembly Shopping Cart — x86 (EMU8086), for a computer architecture course.
Coursework: Compiler Construction, Network & Application Security, Distributed Systems.
Currently learning ML, Deep Learning, Computer Vision, and NLP — building from fundamentals up rather than relying on high-level abstractions.