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Career Profile Talk - Dr Mohamed Zaki

last modified Mar 04, 2016 11:29 AM
Video - Dr Mohamed Zaki, Alliance Big Data and Analytics research lead, gives a career talk profile to Cambridge Unveristy Press Education department. Find out how he came to research in this area and his background studies.

Dr Mohamed Zaki is a research associate at Cambridge Service Alliance. He is leading the Big Data and analytics for service research. 

Mohamed’s key research interests lie in the field of Big Data analytics and its implication on manufacturing, service science and business model innovation. His research uses an interdisciplinary approach of Big Data technology to address a range of real organizations problems to make better business decisions within complex service network. He is working in many research projects in collaboration with business industries such as BAE systems, Caterpillar, IBM, Pearson and Zoetis. Mohamed is also a member of the Steering Board of the Cambridge Big Data Strategic Research at the University of Cambridge. He is a co-investigator in EPSRC research networks such as Consumer Goods, Big Data, and Redistributed Manufacturing (RECODE) and EPSRC-Digital Economy (NEMODE). Recently, he is appointed as a research associate member at St Edmund's College, University of Cambridge.

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Webinar - High-Quality Prediction Intervals for Deep Learning

Jun 11, 2018

11 June 2018 - High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach - by Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely

Theme Update - Blockchains in Smart Services

Jun 06, 2018

In May, Veronica and her team worked very hard on the first practical phase of the project – the Codification of the Blockchain Prototype for the CAT/Perkins’ Supply Chain.

Project Update - OMMS: the Wireless Micro-Factory that will Treat People with Cancer

Jun 06, 2018

The OMMS micro-factory project lead by Dr Veronica Martinez made a great progress this month.

June 2018 Newsletter

Jun 04, 2018

Find out what the Cambridge Service Alliance have been doing and how you can get involved.

Rare-events classification: An approach based on Genetic Algorithm and Voronoi Tessellation

May 31, 2018

by Abdul Rauf Khan, Mohamed Zaki, Henrik Schiøler, and Murat Kulahci. The paper was accepted at 'The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)', a leading international conference in the areas of knowledge discovery and data mining (KDD). In this paper, Mohamed and co-authors propose a novel strategy for data mining based on partitioning of the feature space through Voronoi tessellation and Genetic Algorithm, where the latter is applied to solve a combinatorial optimization problem.

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