Asaduzzaman Noor
About Me Link to heading
I’m a backend‑focused software engineer who crafts reliable, well‑instrumented systems that scale without drama. Proficient in Go and fluent in Linux internals, I thrive at the intersection of data, distributed systems, and pragmatic engineering. Systems programming excites me—designing efficient paths where memory layout, concurrency, and syscall boundaries matter most. For low‑level performance and fine‑grained control, I turn to Zig, building C‑compatible libraries that slip effortlessly into Go services or Python workflows to accelerate critical paths. I wield Python for advanced scripting, data visualization, and AI innovation, and keep my frontend skills just enough to ship with React and TailwindCSS if it’s needed.
Outside of industry work, I published research on semantic segmentation from high‑resolution satellite imagery, exploring patch‑wise modeling and the impact of label noise. Earlier in life, I earned the President’s Scout Award (2010)—a formative experience in leadership and resilience that still shapes how I work.
Preferred Languages Link to heading
- Go
- Python
- Zig
- JavaScript
- Lua
- Bash
Frontend Link to heading
- React
- TailwindCSS
Databases Link to heading
- PostgreSQL
- MySQL
- Amazon DynamoDB
- Redis
- Elasticsearch
- InfluxDB
- DuckDB
Messaging & Task Queues Link to heading
- NATS
- Asynq (Go)
Infrastructure Link to heading
- Linux
- Docker
- Kubernetes
- Pulumi/Terraform
Observability Link to heading
- Grafana
- Prometheus
- Loki
Cloud Computing Link to heading
- AWS
- GCP
Selected Publications Link to heading
- Patch-Wise Semantic Segmentation of Sedimentation from High-Resolution Satellite Images Using Deep Learning. Springer, 2021
- Effect of Label Noise on Multi-Class Semantic Segmentation: A Case Study on Bangladesh Marine Region. Taylor & Francis, 2022
I care about clear interfaces, measurable performance, and operational simplicity. Whether it’s a low‑latency service in Go, a cache‑friendly and/or memory efficient component in Zig, a data pipeline instrumented end‑to‑end, or a small React/Tailwind dashboard to surface the right metrics, my goal is to ship clean, maintainable systems that earn their keep in production.