Qatar Computing Research Institute (QCRI), a national research institute under the Hamad Bin Khalifa University, and Boeing completed the third annual Machine Learning and Data Analytics Symposium (MLDAS) in Qatar.
Open to students, researchers and industry experts, the event, which took place on Monday and Tuesday in Doha featured top global experts discussing applications, recent advances and new solutions in the fields of machine learning and data analytics.
The first day of the symposium was focused on applied data analytics and machine learning. There were several talks on intelligent data analytics led by Chris Jermaine from Rice University and Cheng Soon Ong from Data 61/National ICT Australia (NICTA).
The second day dealt with healthcare and how machine learning can be applied to aircraft maintenance and airspace procedures.
Hugh Durrant-Whyte from the University of Sydney, a pioneer of autonomous flight and former director of NICTA, gave a talk on “Data, Knowledge and Discovery: Machine Learning meets Natural Science,” while Byron Wallace from the University of Texas at Austin spoke about machine learning for automating clinical evidence.
“The remarkable improvement in the quality of research submissions and the international reputation of the invited speakers clearly indicates that MLDAS has established itself as a premier symposium on Data Science. This is a huge success for Qatar and the region,” said symposium co-chair Dr Sanjay Chawla from QCRI.
This symposium continued with the focus on healthcare and saw discussions on applied machine learning for systems health management, trying to address some of today’s research questions, and to discuss the open questions posed by real-world applications.
Topics such as human-system interactive learning, machine learning for streaming data, and integrating learning with other artificial intelligence techniques such as knowledge representation and reasoning dominated the talks and technical discussions.
Dr Dragos Margineantu from Boeing Research & Technology and co-chair of the symposium added: “When we organised the first MLDAS three years ago, we wanted to drive conversations and innovations in the machine learning and data analytics field. Since that time, we have seen unprecedented growth and, though we’re just one piece of a huge field I’m proud that we’ve been involved and helped connect respected researchers with practitioners and students to further advance research in the fields of machine learning and data analytics.”