Projects

Every project I undertake is a step toward building technology that matters — systems that solve real problems, empower teams, and create lasting impact.

Below are select examples of my work at the intersection of cloud architecture, automation, machine learning, and backend engineering — each crafted with care, clarity, and scale.

Serverless Word Splitter Pipeline Link to heading

Technologies: Java, Apache Beam, Google Cloud Dataflow, Cloud Storage
GitHub »

Designed and implemented a scalable serverless ETL pipeline that processes vast amounts of textual data efficiently across distributed cloud systems. This project reflects my commitment to creating elegant, cloud-native solutions that simplify complexity and drive operational excellence.

  • Engineered dynamic autoscaling for optimized batch processing
  • Decoupled compute and orchestration for performance and reliability
  • Leveraged Google Cloud tools for seamless, maintainable deployment

Housing Price Prediction – CI/CD & Cloud Deployment Link to heading

Technologies: Python, Scikit-learn, Docker, Cloud Build, Cloud Run, CircleCI, Locust
GitHub »

Developed a full machine learning lifecycle pipeline — from data modeling to continuous deployment — that delivers real-time housing price predictions via a scalable serverless API. This work embodies my passion for bridging data science and software engineering to bring meaningful insights into production.

  • Trained and validated robust regression models
  • Automated containerized deployments and testing workflows
  • Stress-tested APIs under load for resilience and reliability

ML Bias Evaluation Tool (Research) Link to heading

Technologies: Python, Pandas, Scikit-learn, Streamlit
(Private research repository)

Created an interactive tool that uncovers and visualizes biases in machine learning datasets, fostering responsible AI practices. This research project resonates with my belief that technology must be ethical and accountable to truly serve people and society.

  • Quantified fairness metrics like disparate impact and equal opportunity
  • Visualized complex trade-offs to support ethical decision-making
  • Automated detection to promote transparency and reproducibility

Solar Financial Modeling Automation Platform Link to heading

Technologies: Python, FastAPI, Azure DevOps, PVLib, Dash, Docker
(Internal enterprise project)

Led backend development of a cloud-based platform that automates financial modeling for solar energy projects, replacing manual processes with scalable, secure software. This initiative reflects my dedication to applying technology for sustainability and operational impact.

  • Achieved over 70% reduction in manual engineering effort through automation
  • Built secure, modular APIs supporting dynamic financial calculations
  • Developed custom visualization tools for clear, actionable insights

Bias-Driven ML SaaS Platform Link to heading

Technologies: Python, Docker, Google Cloud SQL, Firestore, AI Platform, Cloud Functions, Cloud Run
Research project »

Built a SaaS platform empowering users to run containerized machine learning experiments and assess bias in real time. This project highlights my drive to democratize advanced ML tools and embed fairness into technology workflows.

  • Enabled automated training and evaluation in three clicks
  • Managed orchestration and state with cloud-native services
  • Supported reproducibility and accountability across protected features

Explore More Link to heading

Curious to see the full range of my work? Feel free to visit my GitHub or connect with me on LinkedIn.

If you’re passionate about building purposeful technology or have an opportunity that aligns with these values, I’d love to hear from you.