Anomaly detection seeks to identify rare and abnormal events that deviate from expected behaviour, a task central to safety-critical domains such as industrial monitoring and energy systems. However, its real-world deployment remains challenging due to co-occurring heterogeneous anomalies, contaminated training data, complex temporal dynamics, and unreliable decision-making thresholds. Sukanya Patra made four complementary contributions in her thesis towards addressing these critical gaps. Her dissertation is supervised by Prof. Souhaib Ben Taieb and Prof. Stéphane Dupont.