معرفی
Professor Tingting Zhu is an Associate Professor in AI for Digital Health at the University of Oxford's Department of Engineering Science. She holds affiliations with Kellogg College as a Non-Tutorial Fellow and Mansfield College as a Stipendiary College Lecturer. Her academic journey includes a DPhil in Information and Biomedical Engineering from Oxford, an MSc from University College London, and a BEng in Electrical Engineering from the University of Malta.
Her research focuses on advancing AI-driven solutions for healthcare challenges, particularly in digital health technologies, electronic health record (EHR) analysis, wearable sensor applications, and interpretable machine learning models. Key areas include arrhythmia detection via ECG, predictive analytics for clinical outcomes, and improving healthcare accessibility in low-resource settings. She leads initiatives in federated learning for privacy-preserving healthcare data analysis and has pioneered frameworks like RapiD_AI for pandemic preparedness.
Professor Zhu's work is supported by prestigious fellowships, including the Royal Academy of Engineering Research Fellowship and recognition as a Fellow of the Academy of Medical Sciences (2025). Her contributions span interdisciplinary collaborations, integrating engineering, computer science, and clinical expertise to address global health challenges. Recent projects include optimizing antibiotic resistance predictions, enhancing ICU mortality prediction models, and evaluating digital health adoption in Vietnamese hospitals.
Her awards reflect her impactful contributions to both academic innovation and practical healthcare solutions. Current research emphasizes scalable AI systems for equitable healthcare delivery, with a focus on low- and middle-income countries. She actively mentors early-career researchers and contributes to policy discussions on ethical AI deployment and data democratization in healthcare.
