Faisal Zafar is deep into neural networks, and programs automated artificially intelligent systems that can forecast financial markets.
Faisal began his interest in computer technology as a young boy when his father bought him his first PC on which he learned basic programming skills. He taught himself the basics of electrical circuits and programming languages. Faisal would go on to attain a Microsoft Certified Systems Engineer certification, as well as both Cisco networking and design certifications. Still his desire for more knowledge in the subjects that held his interest most would lead to his college career and future research. Faisal obtained a Master’s in Computer Science and a Master’s in Business Administration only to continue on to further his education entering in to a Doctoral program in Computer Science. He gained deep insight into the idea of finance and global markets, along with the ease and comfortability he harbored for computer hardware and software.
His interest in financial markets grew when he worked on Wall Street at ILX Systems. Faisal was introduced to the world of global markets and the vast amounts of data they create. At this time an idea occurred to him that an overwhelming advantage can occur in financial markets if there is both the understanding of finance and technology.
These foundations of interest would later shape the areas of research and ultimately the career path for Faisal. He would strive to understand and implement new methods of technology and business understanding of financial markets. With these areas of expertise and research it would fuel his work to create a predictive artificially intelligent system. He would implement a method that would take in vast amounts of real time data as input in to his neural networks for the constructs of his system to accurately predict, trade, and have an overwhelming advantage overthe forex markets. This would not be a small undertaking and as such Faisal has planned, implemented, and continues to test his system only satisfied with near perfect results.
