I am a Certified Cloud Security Architect and an experienced technical lead with over 12 years of experience. I have led teams through the entire Software Development Life Cycle (SDLC), which includes planning, analysis, design, test, build and deployment.
I am an avid proponent of Cloud Computing, Cyber Security, Artificial Intelligence and DevSecOps methodologies. My experience portfolio includes some of Australia’s largest IT projects. I also have experience working with Indigenous organisations in Australia.
Bilal Ahmed
M: 0432 020 777
E: mbilalimpossible@hotmail.com
Stanford University Graduate School of Business, USA, 2016
University of Melbourne, Australia, 2013
Harvard University, USA, 2012
Victoria University, Australia, 2008
University of Melbourne• July 2013
Post graduate thesis on viable techniques for seamless proximity detection in mobile devices. The thesis presents implementation techniques for applications to make use of a device’s location and proximity to other devices to achieve coarse and fine resolution for detection and spatial mapping.
University of Melbourne• May 14, 2013
Twitter with over 500 million users globally, generates over 100,000 tweets per minute. This paper investigates various techniques for lexical normalisation of Twitter data and presents the findings as the techniques are applied to process raw data from Twitter.
University of Melbourne• June 3, 2013
This paper presents a set of experiments which involve the use of prevalent machine learning techniques to build models to predict the day of the week by analysing the weather data. The results provide a comparison of accuracy of these machine learning techniques and their reliability across four cities in Australia {Brisbane, Adelaide, Perth, Hobart}.
University of Melbourne• October 10, 2012
Term paper on RFID and its application in mobile devices with key focus on emerging technologies to address market gaps.
University of Melbourne• April 15, 2012
Published paper on advanced algorithms and techniques to maximise execution efficiency based on job deadline and priority on distributed systems.