CSE student · Web developer · AI explorer

Building useful systems for a smarter future.

I’m Masum Billah, a Computer Science and Engineering student at BUBT. I build responsive web experiences and explore explainable AI, machine learning, data science, and climate-focused computing.

Open to internships, junior roles and collaborations
Portrait of Masum Billah
Masum Billah
Problem solver in progress · Dhaka, Bangladesh

Profile highlights

03Research studies
07 mo.Customer experience
Full stackCurrent learning path
AI + MLResearch direction
About / 01

Curiosity translated into code and research.

My work sits at the intersection of software engineering and intelligent systems. I enjoy turning ideas into responsive products, studying real datasets, and documenting results honestly—including limitations.

Alongside technical work, seven months in customer service at Genex strengthened my communication, teamwork, patience, and ability to solve problems under pressure.

masum@portfolio:~$ profile --summary
education: BSc in CSE · BUBT
building: responsive web applications
exploring: AI · ML · data science
research: climate risk · Green AI
mission: learn deeply, build responsibly
Capabilities / 02

A growing toolkit for real-world problems.

Web development

Responsive interfaces using HTML, CSS, Bootstrap and JavaScript, with full-stack development as my current path.

AI & machine learning

Supervised learning, evaluation, explainability and responsible experimentation with public datasets.

Data & research

Data preparation, statistical thinking, reproducible analysis and clear reporting of evidence and limitations.

Support & teamwork

Customer service, IT support, Microsoft Office, communication and night-shift operations experience.

Research / 03

Evidence before hype.

View all papers
01

Explainable AI for Climate Stress

Early-warning modelling across eight Bangladesh divisional cities.

ROC-AUC 0.923
02

Extreme Rainfall Early Warning

Chronological rare-event testing with a rainfall-risk proxy.

Recall 78.1%
03

Carbon-Aware Model Selection

Choosing efficient models with explicit accuracy-energy trade-offs.

Energy −93.9%
Next signal

Let’s build something meaningful.

Have an internship, junior opportunity, project or research idea? I would like to hear about it.