Hi, I'm Foysal 👋
Software engineer building dependable backends and full-stack products. Based in Dhaka, Bangladesh.
About
CSE graduate with a major in Software Engineering, working across .NET and the TypeScript ecosystem. I care about correctness under load, clean architecture, and systems that fail gracefully. Alongside product work I compete in programming contests and do research when it matches with my interest.
Work Experience
Credosis Apr 2026 - Present Software Engineer Remote · Dhaka, Bangladesh
- Designing and building the in-house API and booking system with ASP.NET Core Web API.
- Built the company frontend with Next.js and TypeScript.
- Supervising software engineering interns during product development.
Deepchain Labs Dec 2025 - Mar 2026 Full Stack Engineer Remote · Dhaka, Bangladesh
- Built multi-tenant auth, workspace creation, sprints and task allocation for Kazentic.
- Designed API endpoints and database structures around business logic.
- Developed sprint-management and time-tracker UI from Figma, wired to the backend.
Education
American International University - Bangladesh 2022 - 2026
BSc in Computer Science & EngineeringMajor in Software EngineeringCGPA 3.61 / 4.00
Skills
C# .NET / ASP.NET Core EF Core TypeScript Next.js NestJS Node.js PostgreSQL MongoDB MSSQL Docker C++
Competitive Programming
Codeforces Pupil Mr_FM
max 1206 550+ problems solved and participated 50+ rated contests.
CodeChef 2★ mr_fm
max 1540 100+ problems solved and participated 20+ rated contests.
Overall
1200+ DSA problems solved across various platforms and participated in 100+ online contests.
- ICPC Dhaka Regional Preliminary 2023 — Team: Aiub_BugBear
- NCPC Regional Preliminary 2023 — Team: Aiub_BugBear
- Intra AIUB Programming Contest 2024 — Mode: Individual
- Web Xtream Hackathon 2025 — Team: Group_15
Research
Robust Multi-Weather Pothole Detection: An Enhanced YOLOv9 Trained on the MWPD Dataset ↗
A published study introducing an enhanced YOLOv9 model trained on the Multi-Weather Pothole Detection (MWPD) dataset for robust detection across adverse weather conditions.
A Two-Stage Object Detection Framework for Autonomous Vehicles ↗
BSc thesis proposing a two-stage object detection framework for autonomous vehicles, built on a custom multi-weather dataset and YOLOv8.
Projects
All projects →Get in touch
Want to talk? Reach me at foysal613@outlook.com or find me on GitHub and LinkedIn.