I have many experiences as following system such as: FAST, Cambodia Shared Switch, Core Banking Functionalities, Inventory management, Hotel, Rental Stall, SuiteCRM, FileMaker project and etc. Recently, I was Software Developer in PowerChoice and I was working on creating modules for supporting CMS and creating tasks in CRM using technology such as: Perl, FileMaker, MySQL, SuiteCRM, ProcessMaker and Apache almost three years now. My previous career, I was also software developer in Mobile C&C for three years. Moreover, I researched bank technology solution and I did some previous projects such as: Core Banking Functionalities, Mobile C&C Home Page, LifeOn, BizMob Portal, Comtus, IRIS Portal and BizMOB square using spring framework with myBatis and SQL Server 2008 and MySQL. Besides, I had three years experiences in website development using either C# ASP.NET or Microsoft SQL Server in AVALDE Company both window base and web based ASP.NET MVC during two years in NetSoft and another one years in BRC Company. Moreover, I excel at: C# .NET Framework and SQL Server Java Spring Framework and MySQL Perl and FileMaker Furthermore, I study and review more about SOA (2016), design patterns, myBatis, spring framework, kendo UI, and scrum methodology, ASP.NET MVC 4.0 in Visual Studio 2013, Bootstrap 3 and AngularJS, FileMaker, Perl, C++, CMake, SWIG and joined ProcessMaker course and others through the eBook. I hope this is helpful to upgrade to new technologies in IT. ©

Experienced Machine (Deep Learning) Learning Specialist with a demonstrated history of working in the statistics, computer vision, and bioinformatics. Data Science Machine Learning Engineering Software Engineer [email protected] CORE COMPETENCIES: ● Fluency in Python, R, SQL, etc. ● ML model development (Computer Vision, NLP) ● Analytical Skills. ● Statistical analysis. ● Software engineering. ● Ph.D. in Bioinformatics ● MA in Applied Statistics. ACCOMPLISHMENTS: â–  Published multiple papers across different disciplines: education, biochemistry, computer science, and statistics. â–  Improved machine learning model performance of more than 5x as measured by accuracy and recall by integrating a video frame data-filtering pipeline and a two-output transfer learning model with CNN and LSTM. â–  Built a statistical base model for an estimate of reference correcting values for protein and surpassed the state-of-the-art performance as measured by reference error below +/- 0.22 ppm at 90% confidence interval. (State of the art is around 1ppm.) â–  Accomplished a state-of-the-art cancer detection and type classification performance as measured by the accuracy of >97% and the false positive/ negative rates of <0.2% by using transfer learning approach. Please contact me at ☏ (857) 209-1002 with any data science, machine learning, deep learning, and software engineering opportunities. ©

My Company: AllesEDV GmbH (). I try to find technical solutions for various problems :-) ©