Research vision
Control for real systems
My vision is to connect mathematical structure with practical energy-system decisions: models that are understandable, controllers that respect physical limits, and evidence strong enough to support the next stage of validation.
Three principles
How the research is framed
Reliable abstraction
Use the simplest model that still preserves the constraints, interactions, and uncertainty that determine a control decision.
Coordinated decisions
Connect long-horizon planning with real-time control while keeping their different time scales, objectives, and operational limits explicit.
Evidence before scale
Test methods progressively, from analysis and simulation to hardware-oriented and experimental validation, before claiming operational relevance.
Research pathway
From modelling to deployment
Model
Define the system boundary, operating assumptions, uncertainty, and measurable states.
Design
Formulate control and optimization methods around the decisions the system must make.
Stress-test
Evaluate stability, constraints, computation, and failure cases across credible scenarios.
Translate
Move validated logic toward implementable architectures with assumptions and limits stated clearly.