IC Colloquium: Data Science for Health: Challenges and Trends
By: Wagner Meira Jr. - Universidade Federal de Minas Gerais
Video of his talk
Abstract
Despite the current enthusiasm associated with the use of data mining and machine learning algorithms, their actual use is still a challenge in several application scenarios and there is a growing awareness of the need for these algorithms to be compatible with ethical, moral, and human values. In this seminar, we argue that employing these models and techniques effectively demands them to be contextualized to the domain, interpretable to end users, and automated as much as possible. We will discuss these requirements and present some recent results we achieved in the scope of healthcare applications, in particular cardiology.
Bio
Wagner Meira Jr. is a Professor of Computer Science at Universidade Federal de Minas Gerais, Brazil. Wagner holds a Ph.D. in Computer Science from the University of Rochester (1997) and is currently a research fellow at CNPq, and a principal researcher at the Brazilian National Center for Innovation in Artificial Intelligence for Health. He has published over three hundred papers in journals and conferences. He is co-author of the books Data Mining and Analysis - Fundamental Concepts and Algorithms (2014) and Data Mining and Machine Learning - Fundamental Concepts and Algorithms (2020), published by Cambridge University Press. His research interests are in parallel and distributed systems, in particular their scalability and efficiency, ranging from massively parallel systems to Internet-based platforms, and in data mining algorithms, their parallelization, and application in areas such as data science, healthcare, cybersecurity, web, and social networks.
Video of his talk
Abstract
Despite the current enthusiasm associated with the use of data mining and machine learning algorithms, their actual use is still a challenge in several application scenarios and there is a growing awareness of the need for these algorithms to be compatible with ethical, moral, and human values. In this seminar, we argue that employing these models and techniques effectively demands them to be contextualized to the domain, interpretable to end users, and automated as much as possible. We will discuss these requirements and present some recent results we achieved in the scope of healthcare applications, in particular cardiology.
Bio
Wagner Meira Jr. is a Professor of Computer Science at Universidade Federal de Minas Gerais, Brazil. Wagner holds a Ph.D. in Computer Science from the University of Rochester (1997) and is currently a research fellow at CNPq, and a principal researcher at the Brazilian National Center for Innovation in Artificial Intelligence for Health. He has published over three hundred papers in journals and conferences. He is co-author of the books Data Mining and Analysis - Fundamental Concepts and Algorithms (2014) and Data Mining and Machine Learning - Fundamental Concepts and Algorithms (2020), published by Cambridge University Press. His research interests are in parallel and distributed systems, in particular their scalability and efficiency, ranging from massively parallel systems to Internet-based platforms, and in data mining algorithms, their parallelization, and application in areas such as data science, healthcare, cybersecurity, web, and social networks.
Practical information
- General public
- Free
- This event is internal
Contact
- Host: Bob West