Hi, I'mSium Ahameed
Bhuyan
Building intelligent systems
from data to deployment.
Statistics × Machine Learning × AI Engineering
$ whoami
sium-ahameed
$ focus
Data Science
Statistical Modeling
$ status
building...
$ whoami
sium-ahameed
$ focus
Data Science
Statistical Modeling
$ status
building...
5+
Featured Projects
8+
Technical Domains
4+
Deployed Applications
4+
Leadership Roles
WHAT I BUILD
Engineering Intelligence
Where statistical reasoning meets intelligent systems. I care about uncertainty, assumptions, inference, and whether a model actually provides reliable evidence.
Machine Learning
Predictive models, classification, regression, clustering, feature engineering, and model evaluation.
Data Science
Statistical analysis, EDA, experimentation, visualization, and predictive analytics.
AI Engineering
AI applications, APIs, LLM workflows, RAG, and intelligent automation.
ML Systems
Model serving, APIs, deployment, pipelines, and reproducibility.
ABOUT
Where Statistics Meets ML
I'm a Statistics student at Dhaka College. My background in statistics influences how I approach machine learning. I care about uncertainty, assumptions, inference, evaluation, and whether a model actually provides reliable evidence rather than simply producing a high score.
I got into AI because I wanted to find patterns that matter. Projects later, I've built text classifiers, data pipelines, full-stack AI apps. Some shipped, some flopped. Each one taught me something I could not get from a textbook.
Right now I'm looking for an internship or research collaboration where I can work on real ML systems with people who know more than me. I learn fastest when there is something real at stake.
My Journey
Quick Facts
Name
Sium Ahameed Bhuyan
Education
BSc in Statistics
Location
Dhaka, Bangladesh
Focus
ML / AI Engineering / Data Science
HOW I BUILD
Engineering Approach
I don't start with the most complicated model. I start by understanding the problem, the data, and the baseline.
Data
Collect and understand the raw data
Clean
Handle missing values, outliers, and types
Explore
EDA, distributions, and correlations
Engineer
Feature creation, selection, and scaling
Train
Baseline models, cross-validation, tuning
Evaluate
Honest metrics, comparison, and analysis
Deploy
API, application, and monitoring
FEATURED WORK
Projects
Selected projects across machine learning, data analysis, and applications.
Heart Disease Prediction
Predicting heart disease risk using classification algorithms on patient medical data with comprehensive model evaluation.
Best Model
XGBoost
F1 Score
0.91
CV Folds
5
BD Road Accident Analysis
Comprehensive analysis of road accident patterns in Bangladesh to identify key causes, trends, and safety recommendations.
BD Temperature & Rain Analysis
Analyzing temperature and rainfall patterns across Bangladesh to identify seasonal and regional climate trends.
PROJECT ARCHIVE
Spam SMS Detection
NLP project to detect spam messages using TF-IDF vectorization and supervised machine learning classifiers.
Rock and Mine Prediction
Predicting whether an object is a mine or rock using Logistic Regression on sonar radar data.
Ad Click Prediction
Predicting user ad clicks using classification models for better targeting and campaign optimization.
Energy Consumption Prediction
Forecasting energy consumption using regression models for better resource planning.
Loan Prediction
Predicting loan approval status based on applicant details using classification algorithms.
IPL Data Analysis
Comprehensive analysis of Indian Premier League cricket data to extract team and player insights.
Diwali Sales Analysis
Analyzing Diwali sales data to understand customer purchasing patterns and product trends.
Shop Data Analysis
Analyzing US retail shop data to understand sales patterns and customer behavior.
Lego Data Analysis
Exploratory analysis of Lego product datasets to explore sets, themes, and trends.
BD Cricket Analysis
Exploratory data analysis of Bangladesh cricket statistics and performance metrics.
TECHNICAL STACK
Skills
Technologies and tools I work with across the ML pipeline.
Where statistics meets machine learning
My stats background means I don't treat models as black boxes. I care about assumptions, inference, and whether a model actually works.
Languages
Core
Data Science
Analysis
Visualization
Machine Learning
ML
AI Engineering
AI
Engineering
Backend
Tools
EXPERIENCE
Where I've Contributed
Leadership and collaborative roles that shaped how I approach problems.
Management Trainee
YSSE
- Led a team of 14 interns across multiple technical initiatives
- Organized technical workshops and IELTS preparation programs
- Contributed to business development strategy and execution
Project Manager
Dhaka College Data Analytics Club
- Managing data analytics projects and workshop sessions
- Coordinating team deliverables and timelines
- Organizing data science competitions and hackathons
Campus Deputy Director
Hult Prize
- Served as campus-level coordinator for the Hult Prize competition
- Promoted social entrepreneurship and impact-driven innovation
- Managed campus outreach and participant engagement
Committee Member
Volunteer for Bangladesh
- Contributed to national-level volunteer coordination
- Participated in community development initiatives
- Supported event planning and logistics
EDUCATION
Academic Foundation
BSc (Honours) in Statistics
Dhaka College
Expected Graduation: June 2027
Relevant Areas
LEARNING
Currently Exploring
Actively learning and experimenting with these areas.
OPEN SOURCE
GitHub Activity
—
Public Repositories
—
Followers
Top Languages
Let's connect
Got a project in mind?
Let's talk.
I'm open to AI/ML internships, research collaborations, freelance projects, and opportunities to build data-driven products.