About
Sonali Parbhoo is a Lecturer in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. She is affiliated with the Artificial Intelligence Network and focuses on AI applications in healthcare, particularly in medical decision-making, causal inference, and interpretable machine learning. Her research bridges machine learning theory with clinical practice, addressing challenges in treatment optimization and safety-critical systems.
Her work emphasizes developing algorithms that integrate human expertise (e.g., clinician input) into AI systems, ensuring transparency and safety. Notable themes include reinforcement learning for treatment policies, causal Bayesian methods for bias mitigation, and concept-driven approaches to model interpretability. Recent projects explore peri-operative risk prediction, vasopressor treatment optimization in sepsis, and biomarker discovery in acute myeloid leukemia.
Parbhoo's publications reflect a multidisciplinary approach, combining machine learning theory with clinical domain knowledge. While no awards are explicitly listed, her prolific output indicates impactful contributions. She collaborates closely with the Department of Electrical and Electronic Engineering's AI research groups and participates in Imperial College's broader AI initiatives.
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