DOHA: Building upon their partnership, Qatar Computing Research Institute (QCRI) and Boeing will co-organise a Machine Learning and Data Analytics Symposium (MLDAS) in Doha in March.
It will focus on applications, advances and new solutions in the fields of machine learning and data analytics. MLDAS will also feature discussions and case studies by industry leaders from around the world.
The deadline for submitting research abstracts has been extended to January 31.
A growing number of challenges exist as data generation has become more abundant and has taken on new forms, structured and unstructured, static and streaming. Machine learning is an expanding research domain where algorithms are developed to learn from data, thus helping to process massive amounts of data through applying predictive techniques.
“Co-organising this symposium with Boeing brings our relationship to a new level,” said Dr Ahmed K Elmagarmid, Executive Director of QCRI. “Our joint work in data analytics research has been focused on addressing specific problems, but this event will provide an open venue to a wider research audience to exchange ideas in an area of science that is growing in importance to science and industry.”
Boeing and QCRI signed an agreement in early 2013 to jointly investigate ways to better recognise patterns, correlations and anomalies in massive amounts of data through machine learning algorithms and data analytics techniques applicable to aircraft maintenance data. This agreement will result in the development of statistical and analytical methods for learning predictors and detectors in plane health management.
“Our collaboration with QCRI broadens and deepens Boeing’s engagement in Qatar, where we already have strong customer and stakeholder relationships,” said Jeff Johnson, President of Boeing Middle East. “Scientists, technology leaders and students from across the globe will gather in Doha to share ideas, identify solutions, and foster partnerships.”
Researchers and students are invited to submit research abstracts related to the domain, and if accepted, will be asked to present their research at the symposium. Submission guidelines and other details about the symposium can be found by visiting www.mldas.org.
Dr Mohammed J Zaki, Principal Scientist, QCRI and symposium co-chair, said, “The symposium features experts in machine learning and data mining. It serves as a launching pad for the data mining, machine learning, and data analytics initiative at QCRI. Partnering with Boeing reflects our two primary goals of cutting-edge science for big data analytics and real-world applications.” The Peninsula
