Hello, I'm


ML Engineer NorthAxisML researcherCivic tech builder

I build machine learning systems and AI products for Bangladesh — from explainable medical-risk models to multi-agent platforms for the garment industry. Third-year CS at BRAC University, focused on making AI useful for underserved communities.

হিমেল INPUT → HIDDEN → OUTPUT Open to AI engineering roles
01. STARTUP

NorthAxis

Co-founder of a Bangladesh-based tech company shipping AI products.

02. INDUSTRY

Ontik Technology

Machine Learning Engineer intern.

03. COMMUNITY

Microsoft Learn

Beta Microsoft Learn Student Ambassador.

0Macro AUC · SPECTRA 2026
0Accuracy · Agrocare
0Research papers
0Projects built
01 / Engineer profile

Building AI for Bangladesh.

I'm Hasanul Banna Himel, a third-year Computer Science undergraduate at BRAC University and co-founder NorthAxis. I work as an ML Engineer intern at Ontik Technology, and previously interned at Headstarter SWE.

My work sits where machine learning meets real constraints: low-resource languages, CPU-only hardware, near-zero budgets, and local payment rails like bKash and Nagad. I care about rigorous evaluation — leakage-free splits, SHAP explanations, honest baselines — and about shipping things people in Bangladesh can actually use.

Make AI accessible to the people it usually leaves out.
himel.py

      
01

Applied ML research

Medical imaging and health-risk prediction — with leakage audits and explainability built in.

02

Computer vision

Plant-disease detection at 98% accuracy and an OCR pipeline that reads textile labels from photos.

03

AI products for Bangladesh

A multi-model AI workspace with local payments and a multi-agent system for the RMG industry.

04

Civic tech

Community problem mapping, offline AI for rural areas, and tools built around local needs.

02 / Featured work

Products at NorthAxis

As co-founder, I lead the technical side of products built for Bangladeshi users and industries — AI-first, with local payments wired in from day one.

NorthAxis · Product suite

From multi-model AI to multi-agent industry tools

Two products, one thread: take capable AI and make it work in the Bangladeshi context — local languages, local payments, local industries.

0Domain agents · RMG
0BD payment rails
0Workspace modes · Axiom
BDTLocal billing
Product stack
Select a product to inspect it.
Research · Health MLPresented · SPECTRA 2026

Maternal Health Risk Classification

Explainable risk-level classification for maternal health. An Extra Trees ensemble reaches a macro AUC of 0.9396, and SHAP shows which clinical factors drive each prediction.

0Macro AUC
SHAPExplainability
Extra TreesSHAPScikit-LearnPandas
Machine learning

Customs Fraud Detection

A fraud-detection pipeline on an NBR customs dataset from Kaggle — engineered features, gradient-boosted models and SHAP explanations, with careful handling of target-encoding leakage.

XGB+ LightGBM
SHAPExplainability
XGBoostLightGBMSHAPPandas
03 / Research

Papers & Presentations

Co-authored research with collaborators at BRAC University and beyond.

04 / Selected works

Things I've built

Machine learning, products, civic tech and apps. Open any card for the details.

05 / Technical expertise

Capabilities

The tools I reach for, grouped by the kind of problem they solve.

06 / Experience & leadership

The Journey

07 / Get in touch

Let's build something that matters.

Open to AI / ML engineering roles, research collaborations, and partnerships with NorthAxis.