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Dr Mohamed Zaki

Dr Mohamed Zaki
Institute for Manufacturing
Department of Engineering
17 Charles Babbage Road

Cambridge , Cambridgeshire CB3 0FS
Office Phone: 01223 332614

Research Themes

Making Big Data Work:

Research Interests

My research interests lie in the field of Big Data advanced modelling and its application on Digital Manufacturing and services. The research uses an interdisciplinary approach of data science techniques to address a range of real organisations’ problems. In particular, my research develops novel data science methods using techniques such as neural network, support vector machine, decision trees, Bayesian networks, genetic algorithm and natural language processing to detect financial frauds, measure customer experience, develop customer loyalty predictive model, analyse machine and sensor data to classify product failures in manufacturing. I commenced my PhD in Data Science at the University of Manchester and my thesis investigated the impact of employing different machine learning algorithms to detect frauds in the stock exchange markets. I am currently leading the Big Data and analytics for service and digital manufacturing research at the Institute for Manufacturing, Department of Engineering, University of Cambridge. Also, I am a research manager and co-investigator in many UK research councils projects (EPSRC/ESRC) and industrial research projects sponsored by big organisations such as IBM, Cisco, BAE Systems, Caterpillar, Rolls Royce, Zoetis, Pearson, GEA Food Manufacturer. I am a core academic member in the Cambridge ESRC Doctoral Training Partnership (DTP) and the EPSRC research network- Consumer Goods, Big Data, and Redistributed Manufacturing (RECODE). Also, I am a recipient of an international award from the Marketing Science Institute on customer experience analytics. I am a steering committee member at the University of Cambridge Big Data Research Initiative. I am creative and innovative with a substantial experience in designing, leading, and implementing a broad range of Big Data research projects. Highly motivated and an excellent communicator, with knowledge and skills for making successful and often highly prestigious research and industrial funding bids (£1,042,260), as my CV indicates. I have a number of publications in highly ranked journals, including PloS ONE, Journal of Service Research, International Journal of Operations and Production Management, Journal of Service Marketing as well as many IEEE conference articles.

Keywords

Text Mining ; Big Data ; Business opportunities in manufacturing Big Data ; Capturing value from Big Data ; Data-Driven business model ; Analytics ; Data governance ; Data Mining ; Manufacturing Analytics

Key Publications

  • Wyllie, Jessica, Benjamin Lucas, Jamie Carlson, Brent Kitchens, Ben Kozary, and Mohamed Zaki (2016), “An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media,” PloS ONE, 11 (10), e0163914.
  • Hartmann, Philipp Max, Mohamed Zaki, Niels Feldmann, and Andy Neely (2016), “Capturing Value from Big Data - A Taxonomy of Data-Driven Business Models Used by Start-Up Firms,” International Journal of Operations & Production Management, 36 (10), 1382-1406.
  • Timothy Keiningham, Joan Ball, Sabine Benoit, Helen L. Bruce, Alexander Buoye, Julija Dzenkovska, Linda Nasr, Yi-Chun Ou, and Mohamed Zaki, “Conceptualizing Customer Experience through a Customer Commitment Lens” is Accepted to Journal of Service Marketing (forthcoming).
  • Zaki, Mohamed, Bøe-lillegraven, T., and Andy Neely (2016). A Transition Towards a Data-Driven Business Model (DDBM): A Case Study of Nettavisen Online Newspaper Publishing. SAGE Publishing. Doi: http://dx.doi.org/10.4135/9781473970113.
  • Zaki, Mohamed (2015). Is Big Data still big news, IfM Review, Vol 3, pp 13-16, available at http://www.cam.ac.uk/research/discussion/is-big-data-still-big-news.
  • Villarroel Ordenes, Francisco, Babis Theodoulidis, Jamie Burton, Thorsten Gruber, and Mohamed Zaki (2014), “Analyzing Customer Experience Feedback Using Text Mining: A Linguistics-Based Approach,” Journal of Service Research, 17 (3), 278-295. The paper has been selected as one of four finalists for the Journal of Service Research Best Article Award for 2014. Also, it has been selected to be one of must-reads article of Marketing Science Institute (MSI) available at: http://www.msi.org/articles/must-read-journal-articles-from-2014/.
  • Zaki, Mohamed, Theodoulidis, Babis, and David Díaz (2011). “Stock-touting” through spam e-mails: a data mining case study. Journal of Manufacturing Technology Management, 22(6), 770–787. Doi: 10.1108/17410381111149639.
  • Duggimpudi, R., Abdou, H., and Mohamed Zaki (2010). An evaluation of equity diversified mutual funds: the case of the Indian market. Investment Management and Financial Innovations, 7(4), 77–84. 

Other Publications

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