This research uses AI to detect subtle interactions between the Higgs boson and muons at the Large Hadron Collider. By refining large datasets, it aims to uncover how particles acquire mass at smaller scales. Confirming this interaction would deepen understanding of the Higgs field and fundamental physics.

This research examines how prior victim or defendant status influences courtroom outcomes. Using Philadelphia court data, it finds that individuals with dual roles receive different treatment depending on context—leniency as defendants but weaker outcomes as victims. The findings challenge assumptions of neutrality and raise concerns about fairness and consistency in the justice system.

This research shows that pauses in information streams alter decision-making. After a break, the brain increases effort, giving greater weight to subsequent information—a “peak-after-break” effect. A computational model explains this as a performance-effort tradeoff. Findings challenge traditional theories and suggest strategic pauses can shape attention, memory, and judgment.

This research uses spatial transcriptomics to map interactions between T cells, cancer cells, and immunosuppressive cells in tumours. Findings suggest cancer suppresses immune responses by surrounding and weakening T cells. The work aims to improve immunotherapy and enable personalised cancer treatment through detailed tumour mapping.

This research develops the Remnant Emission Survey Tool (REST) to identify dormant comets—objects that resemble asteroids but may contain ancient solar system chemistry. By analyzing archived images of 3,800 asteroid candidates for faint gas emissions, REST aims to improve classification and deepen understanding of planetary formation and solar system history.