Institution profile

University of Newcastle

Academic institutionaustralasia · au
Official website
Research library82linked papers
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Selected work

Representative Papers

Exploring GPT-4 for Robotic Agent Strategy with Real-Time State Feedback and a Reactive Behaviour Framework

Mar 30, 2025

Deploying large language models (LLMs) for embodied humanoid robots faces four key challenges: safety assurance, seamless cross-task transition, multi-timescale task adaptation, and closed-loop state feedback. Method: We propose a GPT-4–empowered hierarchical control framework integrating prompt engineering, real-time sensor feedback, hierarchical behavior state machines, and dynamic re-planning to enable reliable, goal-directed subtask decomposition and execution in both simulation and real-world settings. Contribution/Results: This work is the first to systematically address safety-constrained LLM deployment for embodied agents, ensure task-transition consistency, and close the perception–decision–action loop. Experiments demonstrate 100% executable subtask generation across all timescales, jitter-free task switching, and significantly higher user-goal success rates versus baseline methods—substantially enhancing the practical deployability of LLM-driven robots in real-world scenarios.

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Towards a unified approach to formal risk of bias assessments for causal and descriptive inference

Aug 22, 2023

This paper addresses the lack of a unified framework for assessing systematic error (bias) across causal and descriptive inference. We propose the first cross-paradigm, generalizable bias risk assessment method, integrating modeling assumptions, data-generating mechanisms, and inferential objectives to cover high-risk settings—including randomized controlled trials (RCTs), nonprobability sampling, and statistical extrapolation—beyond traditional medical RCT constraints. Our approach combines qualitative bias mapping, assumption sensitivity analysis, and standardized reporting criteria, mandating explicit documentation of untestable assumptions and model uncertainty. The framework has been adopted as a mandatory reporting requirement by leading journals and funding agencies, thereby enhancing the reliability, interpretability, and external validity of research findings. (132 words)

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Recent publications

Latest Papers

Improving the Energy Efficiency of High Throughput Computing: A Measurement-Based Case Study

Aug 06, 2026

This study addresses the challenge of optimizing server energy efficiency in high-throughput computing environments, where performance and energy consumption are often at odds. Leveraging real-world operational data and targeted experiments, the work systematically investigates how server configurations influence power consumption, performance, and carbon emissions, uncovering key barriers to implementing effective energy-saving measures in practice. Through empirical power monitoring, workload modeling, and carbon footprint assessment, the authors identify critical factors governing energy efficiency and propose a practical configuration strategy that simultaneously ensures performance guarantees and advances low-carbon objectives. Evaluated under representative high-throughput workloads, the proposed approach achieves substantial reductions in both energy use and carbon emissions.

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