Projects
Selected research and engineering projects spanning energy systems control and adaptive biomedical sensing. Each case study links methodology, evidence, and outcomes.
The projects below trace a methodological thread: from model predictive control for microgrid frequency regulation, through data-driven system identification with Bayesian uncertainty quantification, to adaptive sensing and closed-loop discovery for biomedical applications. Earlier energy-systems work is presented as transferable evidence; current biomedical projects are ongoing.
See the Research page for the program overview, the Methods page for the four methodological pillars, and the Publications page for the complete publication record.
Adaptive Radar-Based Physiological Sensing
Sequential radar measurement selection to maximise information about physiological signals under real-time and physics constraints.
Closed-Loop Discovery for Synergistic Antibacterial Combinations
Uncertainty-aware active experiment selection for antibacterial combination discovery, with expert review gating for safety.
SINDYc and MCMC for Prosumer Response Estimation
Sparse identification of prosumer dynamics (SINDYc) with Bayesian MCMC uncertainty quantification for interpretable, risk-aware energy models.
Three-Level Hierarchical Microgrid Control
Three-level hierarchical microgrid control architecture validated on a hardware-in-the-loop laboratory platform.
Target-Adjusted MPC for Microgrid Frequency Control
Target-adjusted Model Predictive Control for microgrid frequency regulation under uncertain renewable generation and load.