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Professor Xiaohua Ji is a distinguished academic and Chair Professor in Data Science at Queen's University Belfast. Her research focuses on advancing artificial intelligence, machine learning, and data science, with a strong emphasis on applications in healthcare, biomedical signal processing, and intelligent systems. She is dedicated to developing innovative algorithms and methodologies to extract actionable insights from complex data, aiming to address real-world challenges and improve societal well-being. Professor Ji has a substantial track record of leading high-impact research projects and mentoring a new generation of data scientists.
Xiaohua Ji's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Elected as an IEEE Fellow for contributions to signal processing and machine learning for healthcare.
Holds a prestigious Chair Professorship at Queen's University Belfast, recognizing her leadership and expertise in the field of Data Science.
Successfully secured and led numerous significant research grants from funding bodies like EPSRC, Innovate UK, and others, driving cutting-edge research in AI and healthcare technologies.
Authored and co-authored a large number of influential papers in top-tier journals and conferences, significantly contributing to the body of knowledge in AI, machine learning, and signal processing.
Plays key roles in various research centers and initiatives, fostering collaboration and advancing the application of AI and data science in critical sectors.
复旦大学 - Year 2001
中国科学技术大学 - Year 1996
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果壳网 (Guokr.com) is a leading Chinese online platform dedicated to popularizing science and technology. It provides engaging and accessible content across various scientific disciplines, including physics, biology, technology, psychology, and health. Guokr aims to foster a spirit of inquiry and critical thinking among the public through high-quality articles, Q&A forums, interactive discussions, and offline events. It's known for debunking myths, explaining complex scientific concepts in simple terms, and connecting scientific knowledge to everyday life.
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