Machine learning and data science
This research theme harnesses data's power to make informed decisions and build intelligent systems. With a strong foundation in machine learning algorithms, statistical methods, and computational frameworks, the research explores avenues for optimising operational efficiency and deriving actionable insights from complex datasets. Applications range widely, from transport logistics and urban planning to healthcare analytics and renewable energy systems.
Interdisciplinary at its core, the theme aims to produce models that are not only robust and accurate, but also interpretable and ethical. Collaborations with industry leaders and governmental organisations are integral to our research, as they provide real-world problems that often lead to transformative solutions. By marrying theoretical rigour with practical relevance, machine learning and data science serve as a catalyst for innovation, driving both technological advancements and policy changes for a sustainable future.
Interdisciplinary at its core, the theme aims to produce models that are not only robust and accurate, but also interpretable and ethical. Collaborations with industry leaders and governmental organisations are integral to our research, as they provide real-world problems that often lead to transformative solutions. By marrying theoretical rigour with practical relevance, machine learning and data science serve as a catalyst for innovation, driving both technological advancements and policy changes for a sustainable future.
Contact
Francisco C P D Camara Pereira Professor, Head of Section Department of Technology, Management and Economics Phone: +45 45251496 camara@dtu.dk