Artificial intelligence and computer science research focused on decision-making, explanations, reasoning and intelligent systems.
Methods that make AI-supported decisions more understandable, inspectable and useful to people.
Systems that connect sensing, reasoning, decision-making and action.
Retrieval, precedent, rubric-based evaluation, memory and explanation around language models.
Adaptive systems that use context to guide behaviour in IoT and ubiquitous computing environments.
Combining learning, structured reasoning, uncertainty and user-facing explanations.
Judging, retrieval-supported evaluation and evidence-aware approaches for model outputs.
Hybrid retrieval and case-based memory for rubric-guided LLM evaluation, explanation and revision.
Research connecting perception, retrieval, optimization, explanation, agents and decision execution.
Adaptive and resilient context-aware mechanisms developed through doctoral research.
Research involving resource-aware intelligence, optimization and adaptive system behaviour.