About Me
I'm a passionate Data Science Engineer with a strong foundation in Computer Science and growing expertise in SQL Server, Python, predictive analytics, and data-driven storytelling. Currently pursuing my Master's in Data Science at the University of Sydney, I thrive on transforming complex datasets into actionable insights that drive smarter decisions.
Data Engineering
Building scalable data pipelines, ETL processes, and data warehouses
Automation & Workflows
Designing intelligent automation systems that optimize business processes
AI/ML Engineering
Developing and deploying machine learning models at scale
My Journey
Master's in Data Science
Pursuing advanced studies in data science, machine learning, and predictive analytics
Data Engineer
Built relational databases, designed robust triggers, and worked with real-world datasets
Secretary, IEEE GRIET SB
Led technical projects and organized events, honing leadership and organizational skills
Technologies & Tools
Featured Projects
A selection of projects showcasing my expertise in data engineering, automation, and AI/ML
Dashboards & Visualizations
Interactive dashboards and data visualizations that drive decision-making
Sales Analytics Dashboard
Real-time sales performance tracking with predictive analytics
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<iframe src="https://placeholder-embed.com" />These dashboards are built using modern BI and visualization tools
AI/ML Experiments
Research projects, Kaggle competitions, and experimental ML models
Trained a custom YOLOv8 model on a dataset of 50,000+ images. Implemented data augmentation, transfer learning, and model optimization techniques. Deployed as a FastAPI service handling 100+ FPS on GPU.
Implemented a custom transformer architecture for time series forecasting. Compared performance against LSTM, GRU, and Prophet models. Achieved 20% improvement in RMSE over baseline models. Used for demand forecasting in production.
Fine-tuned BERT-base model on custom dataset of 100K+ reviews. Implemented efficient inference pipeline using ONNX Runtime. Achieved 92% F1-score across 5 sentiment classes. Processes 1000+ documents per second.
Built a hybrid recommendation system combining collaborative filtering and content-based approaches. Used neural networks to learn user and item embeddings. Improved click-through rate by 35% in A/B tests.
Implemented multiple anomaly detection algorithms including Isolation Forest, Autoencoder, and LSTM-based approaches. Compared performance and selected best model for production. Reduced false positives by 60%.
Fine-tuned Stable Diffusion model on custom dataset for generating domain-specific images. Implemented LoRA for efficient fine-tuning. Created web interface for easy experimentation. Generated 10,000+ high-quality images.
Competitions & Achievements
Blog & Articles
Sharing insights, tutorials, and lessons learned from building data systems
Building Scalable Data Pipelines with Apache Airflow
A comprehensive guide to designing and implementing production-ready data pipelines that scale to millions of records.
MLOps Best Practices: From Notebook to Production
Learn how to take your ML models from Jupyter notebooks to production-ready systems with proper monitoring and versioning.
Automating Cloud Infrastructure with Terraform
How to implement Infrastructure as Code to automate and manage your cloud resources efficiently.
Real-Time Stream Processing with Apache Kafka
Deep dive into building real-time data streaming applications using Kafka and Spark Streaming.
Fine-Tuning Large Language Models for Domain Tasks
A practical guide to fine-tuning LLMs like BERT and GPT for specific business use cases.
Data Quality: The Foundation of Reliable Analytics
Implementing data quality checks and monitoring to ensure your analytics are built on solid foundations.
CI/CD for Data Pipelines: A Modern Approach
How to implement continuous integration and deployment for your data engineering workflows.
Computer Vision at Scale: Lessons Learned
Practical insights from deploying computer vision models in production serving millions of requests.
Cost Optimization Strategies for Cloud Data Warehouses
Proven techniques to reduce your cloud data warehouse costs without sacrificing performance.
Let's Work Together
Have a project in mind or want to discuss data engineering, automation, or AI/ML? I'd love to hear from you!
Get in Touch
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.
Ready to Build Something Amazing?
Let's turn your data challenges into opportunities for growth and innovation.