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Member since April, 2011
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Muhammad Muaz

Online Offline
I am coder with experience in Android Programming, HTML, AJAX, JAVA, ExtJS, JavaScript,C, C++, XML, Excel, MySQL, PHP, Google App Engine, Google Web Toolkit and jQuery. With this skill set of developing mobile apps, websites and applications, I can automate any task or process. My skills also extend to graphic design for the past decade. I am able to re-create almost anything I see and create original content.
$50 USD/hr
5 reviews
  • 100%Jobs Completed
  • 100%On Budget
  • 100%On Time
  • 25%Repeat Hire Rate


Recent Reviews

  • image of Fbonny Developpement OCR 2 $500.00 USD

    “Very professional Guy. Good delivery regarding the complexity of the solution. I recommend ! ;-))”

  • image of JHU Javascript and php programming to translate OOP matlab code. $105.00 USD

    “Awesome job well done.”

  • image of mndrk Hand (finger) tracking $450.00 USD

    “Very positive. He has been really flexible in adapting to unusual task. Really good”

  • image of dangioffre1 DJ Website Cheap. $220.00 USD

    “Did he a good job. He was very helpful. He kept on asking me if I wanted anything changed. So he kept me updated with everything. I would hire again.”

  • image of dangioffre1 DJ Banner.. $30.00 USD

    “The Banner was awesome. Great Banner. Thanks. Will hire again.”


Religious Applications on Android

Jul 2012 - Aug 2012 (1 month)

I made Religious application you can see the link here Also I made this

I made a dynamic website with implementation of Internationalization

Nov 2011 - Sep 2012 (10 months)



2008 - 2012 (4 years)


Dean Merit List (2012)

University of Management and Techonolgy

Dean Merit List Award is given to Best Students of the Semester who have perform well in Co-curricular activities.


Human Fall Detection

Fall-induced injuries are common in the elderly population. Delay or lack of medical care after the occurrence of a fall often results in injuries, sometimes severe, and can also lead to death in some cases. Falls, therefore, are critical occurrences for the elderly. Detecting falls automatically, as they occur, can lead to better timed medical care which can in turn reduce the subsequent medical complications. In this paper we describe an effective fall detection system based on videos dataset generated us


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