Mohamed Ibrahim
About Mohamed Ibrahim
Mohamed Ibrahim serves as a Director at the Financial Industry Regulatory Authority (FINRA) in Rockville, Maryland, where he has contributed to the organization's strategic direction since 2016. He holds a PhD in Pattern Classification and Machine Vision from the University of Miami and has extensive experience in software engineering and research within financial regulatory environments.
Work at FINRA
Mohamed Ibrahim has been serving as a Director at the Financial Industry Regulatory Authority (FINRA) since 2016. In this role, he has contributed to the organization's strategic direction and has held various leadership positions. His tenure at FINRA has included responsibilities that align with the regulatory needs of the financial industry. Additionally, he has worked as a Lead Developer at FINRA since 2013, demonstrating a long-standing commitment to the organization and its mission.
Education and Expertise
Mohamed Ibrahim holds a Bachelor of Science in Computers & Systems Engineering from Ain Shams University, where he studied from 1991 to 1997. He furthered his education at the same institution, earning a Master of Science in Network Security from 1997 to 2000. He also obtained a PhD in Pattern Classification and Machine Vision from the University of Miami, completing his studies from 2001 to 2005. His educational background equips him with expertise in problem-solving within financial regulatory environments.
Professional Background
Prior to his current roles at FINRA, Mohamed Ibrahim worked as a Senior Software Engineer at AddThis for eight months in 2012-2013. He also served as a Senior Research Engineer at Fidelis Security Systems from 2006 to 2010. Earlier in his career, he worked as a Research Engineer and Consultant at Global Enterprise Technologies in 2005. His diverse experiences in software engineering and research have contributed to his technical proficiency.
Achievements in Algorithm Development
During his professional career, Mohamed Ibrahim has developed tailored algorithms utilizing optimized probabilistic and statistical implementations. This work reflects his technical skills and ability to apply complex concepts in practical settings, particularly within the financial regulatory framework.