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I build intelligent systems, from machine learning models to agents and full-stack applications.
I design and build AI systems across the full stack, from data and models to agents, APIs and intelligent applications.
Meet RahulBuilding energy forecasting with approximately 26.5M observations. Test R² ≈ 0.983 (XGBoost · raw electricity target).
02 / AGENTIC AI & FULL-STACK SYSTEMSAgent orchestration, retrieval, persistent state, FastAPI backends and React interfaces, with human approval built into the workflow.
03 / COMPUTER SCIENCE FOUNDATIONSComputer Science at UNSW, Sydney. Work spanning machine learning research, software engineering and intelligent automation.
From millions of building observations to a clearer picture of tomorrow’s energy demand.
Explore the researchReported research results · target units not supplied
Coordinates the workflow and maintains task state across specialist agents.
A coordinated agent workflow for discovering opportunities, understanding requirements and tailoring applications with human approval.
Explore the systemFeature: account sign-in Expected behaviour: A user with valid credentials can access their dashboard.
Turning product knowledge into test scenarios, test cases and executable Selenium scripts.
Explore the pipelineTHE NEXT CHAPTER
From requirement to production through autonomous engineering agents. A platform in development, built around persistent memory and human approval.
Follow the buildCoordinates specialists against shared specifications and persistent project memory.
Good AI engineering connects data, intelligence and a product people can actually use.
HOW I BUILD AI SYSTEMS
Understand the user’s actual problem, constraints and definition of success before choosing a model.
I design and build AI systems across the full stack, from data and models to agents, APIs and intelligent applications.
My work spans building energy forecasting, transformer models, multi-agent workflows and retrieval-augmented test automation. The common thread: making the pieces work as a complete system.
More about my approachEnergy forecasting across hourly demand, weather and building context.
Transformer iterations, aligned targets and the engineering of model fusion.
Retrieval as the foundation for grounded application workflows and test automation.
The tools behind the work.
Organised by what they make possible.
Artificial intelligence, machine learning, software engineering and data systems. Thesis: AI-Based Energy Management in Building Operation: Integrating Renewable Energy.
2020–2022. University study before transfer to UNSW.
Ask about the projects, the tools,
or how the pieces fit together.
What would you like to know?
AI engineering · Research · Thoughtful collaboration
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