Ganguli Kaluarachchi

Data Science Undergraduate

01 / HELLO

Ganguli
Kaluarachchi

Data Science Undergraduate

Data Science Machine Learning Applied AI Software Development

I work at the intersection of data, machine learning and software — turning messy information into useful insights and practical digital solutions.

COLOMBO / SRI LANKA

01
Ganguli Kaluarachchi
DATA ML AI
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02
Ganguli Kaluarachchi

02 / ABOUT

A little about
what I do.

I'm a final-year Data Science undergraduate passionate about turning data into meaningful insights and building practical software solutions.

I enjoy working with machine learning, data analytics and applied statistics to solve real-world problems. Alongside data science, I have a growing interest in software engineering and have developed web and mobile applications using technologies including Flutter, Python and JavaScript.

I enjoy challenging myself, collaborating with others and building solutions that have practical value. I'm currently looking for opportunities where I can apply my skills while continuing to grow as a Data Scientist and Software Engineer.

Location Colombo, Sri Lanka
Focus Data Science
Interests ML / AI / Analytics
Status Open to Opportunities
Download full CV

03 / EDUCATION

Academic background.

My formal academic path and the foundation behind my work in data, computing and technology.

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2023 — 2027

Sri Lanka Technology Campus (SLTC)

BSc. (Hons.) in Data Science

Data Science Machine Learning Software Engineering
Current
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2016 — 2021

Walisinghe Harischandra National College

Advanced Level - Physical Science

Combined Mathematics Physics Chemistry

04 / SKILLS

Tools behind the work.

Technologies and concepts I use across data science, analytics, machine learning and software projects.

Soft Skills

Team Collaboration Problem Solving Communication Adaptability Critical Thinking

05 / SELECTED WORK

Projects worth talking about.

A selection of academic and technical work spanning explainable AI, big data, business intelligence and MLOps.

01
Explainable AI Postpartum Depression Mobile Health System Ongoing
Research Project / Group

XAI-Powered Mobile Health System for Postpartum Depression

Final-year research project designing an Explainable AI-integrated conversational mobile health system for early detection and personalized recovery support of postpartum depression among Sri Lankan mothers.

The system combines risk prediction, SHAP-based explainability, conversational symptom check-ins and personalized guidance through a mobile application.

Explainable AI SHAP Dialogflow CX Flutter Supabase
02
SmartCrop ANN-Based Seasonal Crop Recommendation System Completed
Deep Learning / Agriculture

SmartCrop — ANN-Based Seasonal Crop Recommendation System

Developed a Sri Lanka-focused seasonal crop recommendation system combining district-level soil information with forecast weather conditions to recommend suitable crops for farmers.

Built a multiclass Artificial Neural Network using soil NPK, temperature, humidity, pH and rainfall, integrated an LSTM weather forecasting model, compared the ANN with traditional machine learning baselines and developed a farmer-friendly web system.

Python ANN LSTM TensorFlow Scikit-learn Flask React
03
SmartCare Hospital 30-Day Patient Readmission Prediction Completed
Machine Learning / Explainable AI

SmartCare Hospital AI — 30-Day Patient Readmission Prediction

Developed an explainable AI system to predict whether a hospital patient is at risk of being readmitted within 30 days using clinical, admission, utilization and billing data.

Built and compared multiple machine learning models, extended the analysis with deep learning and ensemble methods, used SHAP for model explainability and developed a Streamlit prototype for patient-level risk assessment.

Python Scikit-learn XGBoost TensorFlow SHAP Streamlit
04
Graph Neural Networks for Node Classification on OGBN-Arxiv Citation Network Completed
Graph Neural Networks / Deep Learning

Graph Neural Networks for Node Classification on the OGBN-Arxiv Citation Network

Developed a large-scale graph learning pipeline for multiclass node classification on the OGBN-Arxiv scientific citation network containing 169,343 papers, more than 1.16 million directed citations and 40 subject categories.

Implemented and evaluated GCN and GraphSAGE architectures using PyTorch Geometric, explored learned embeddings and neighbourhood influence, and developed a Streamlit graph intelligence dashboard for graph analysis and model evaluation.

Python PyTorch PyTorch Geometric GCN GraphSAGE NetworkX Streamlit
05
Retail Business Intelligence Case Study
BI / Forecasting

Retail Sales Business Intelligence & Forecasting

End-to-end Business Intelligence case study using more than 307,000 warehouse and retail transactions from 2017 to 2020.

Performed statistical testing, correlation analysis, forecasting and association-rule analysis before translating the findings into a Power BI dashboard.

Python SARIMA Statistics Power BI
06
Telco Customer Churn MLOps Pipeline
MLOps Pipeline / Group

Telco Customer Churn Prediction — Full MLOps Pipeline

Built a production-oriented churn prediction workflow covering data versioning, experiment tracking, orchestration, model deployment and automated retention recommendations.

The project used DVC, MLflow, Apache Airflow, Docker, FastAPI and an LLM-based recommendation component.

MLflow DVC Airflow FastAPI Docker LLM
07
Retail Analytics Pipeline Completed
Big Data Pipeline / Group

Retail Analytics Pipeline — Medallion Architecture

Built an end-to-end Big Data pipeline on more than 540,000 UK e-commerce transactions using PySpark and MongoDB Atlas.

Implemented Bronze, Silver and Gold layers, rule-based data quality validation, duplicate detection, RFM customer segmentation and optimized MongoDB indexes.

PySpark MongoDB ETL Big Data

06 / EXPERIENCE

Leadership beyond the classroom.

Leadership, volunteering and teamwork have been an important part of how I developed professionally.

01
2025 — 2026 IEEE WIE SLTC / Executive Committee

Vice Chairperson

  • Guided and supported technical, outreach and community initiatives including WIE Day, VioletGlow, BlenderOps, WiSTEM and InspiHER{Tech}.
  • Mentored organizing committees and coordinated planning with the executive committee.
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2024 — 2025 IEEE WIE SLTC / Sub Committee

Finance Deputy Head

  • Supported budgeting, financial planning, resource allocation and event coordination.
  • Led WIE Day '25 as Chairperson, organizing a cybersecurity awareness workshop for more than 50 participants.
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IEEE / University Organizations

Other Organizing Committee Experience

Held multiple leadership and organizing positions across IEEE organizations and university societies, supporting project planning, finance, documentation, stakeholder coordination and event execution.

Chairperson Treasurer Assistant Secretary Finance

07 / CREDENTIALS

Professional qualifications & certifications.

Professional certifications, technical credentials and recognized achievements that support my academic and professional development.

01
IEEE

IEEEXtreme 19.0 Programming Competition

Participated in IEEEXtreme 19.0, IEEE's global 24-hour programming competition, as a member of Team Pixelle.

View Certificate

08 / CONTACT

Have something
interesting?
Let's talk.

I'm open to internships, junior data opportunities, software roles and research collaborations.