Mustafa Eisa

Mustafa Eisa is a computational mathematician with a strong interest in statistical learning, artificial intelligence, and diverse applications. He has a rich background in the technology sector of Silicon Valley and has also engaged in consulting internationally and with quantitative funds on Wall Street.

Mustafa's academic journey includes studying various branches of applied mathematics at prestigious institutions such as Berkeley and the University of Chicago, where he even published his master's thesis with Lars Hanson, the 2013 Nobel Laureate in economics and finance. He pursued his PhD coursework in mathematical optimization at Berkeley and later shared his knowledge by teaching machine learning at the Haas School of Business at Berkeley.

On a lighter note, Mustafa finds joy in photography and tackling intriguing math problems. His insights on statistics, mathematics, and artificial intelligence can be explored on his Medium blog and Stack Exchange, where he holds a position in the top 15% for statistics.

Mustafa Eisa's professional experience includes roles such as Lead Data Scientist at enaible Inc., Lecturer at the University of California, Berkeley, Haas School of Business, Senior Data Scientist at Workday, Data Scientist at CBJ Global, Data Scientist at EverString, and Artificial Intelligence Researcher at the University of California, Berkeley. Additionally, he gained experience in the finance sector through a Private Equity Internship at Merrill Lynch.