Entrepreneur | Computer Science | Social Media

My Experience

Data Center Pre Sales Consultant

Five years ago, working in ANTEL, the state telecommunications company of Uruguay, as Data Center Pre Sales Consultant, developing strategies and processes to selling data center solutions for enterprise customers.


I worked as a teacher at Universidad de la Republica, Centro de Educación Técnico Profesional and Universidad Católica del Uruguay involving object-oriented programming, database fundamentals and Java technologies.


I'am a MBA student at Universidad Católica del Uruguay

Web Developer & DBA PostgreSQL

I worked as web developer in Intendencia de Montevideo, performing analysis, design and implementation of websites using PHP. Also I made the administration of the database for the storage of construction of buildings, focusing on its design and maintenance. Other tasks I did: IT consultants, network management and negotiations with suppliers.

Windows Azure Developer

I Participate in the design and development of the migration of a banking platform developed using different Microsoft technologies to Windows Azure, achieving a mature product. Was obtained vast knowledge of the Microsoft cloud platform and a quick guide to making Windows Azure as part of business processes of companies.


Since childhood I have marketed electronic items and computers for national and international customers.

About Me

Martin Rodriguez

Martin Rodriguez B.S. in Computer Science

I define myself as an entrepreneur and seeker of new challenges, who want to learn constantly. Based on a solid experience in the world of technology and software development, I am looking for new challenging projects. Never think you can beat me in uberstrike!!!

My Publications


Facial Recognition Using Neural Networks over GPGPU

The article introduces a parallel neural network approach implemented over Graphic Processing Units (GPU) to solve a facial recognition problem, which consists in deciding where the face of a person in a certain image is pointing. The proposed method uses the parallel capabilities of GPU in order to train and evaluate a neural network used to solve the abovementioned problem. The experimental evaluation demonstrates that a significant reduction on computing times can be obtained allowing solving large instances in reasonable time. Speedup greater than 8 is achieved when contrasted with a sequential implementation and classification rate superior to 85% is also obtained.

Contact Me

Contact Info

Martin Rodriguez
Montevideo, Uruguay
Phone: (+598) 99 13 83 01
Email: getintouch@martiningenia.com
Web: www.martiningenia.com

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