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“Digital Assets are fascinating to me because they are the manifestation of Satoshi’s ingenious solution to a problem in computer science that many believed was impossible to solve—the double-spending problem.”

Ahmad received his MEng degree in Electrical and Electronic Engineering from Imperial College London in 2017 where he made the Dean's list in his final two years and was awarded the Governor's Prize for academic excellence. Here Ahmad focused mainly on data, signals and programming, developing several patents and fulfilling internship roles at General Electric and Bank of America Merrill Lynch. Whist Ahmad realised his passion for data science and research, he knew he wanted to work with companies who were applying the latest breakthroughs in machine learning.

Currently, Ahmad is pursuing a PhD at Imperial College in Machine Learning and Signal Processing. His research is focused on the boundary between extracting latent information from multidimensional data and neural networks. Ahmad has published multiple peer-reviewed papers in areas such as signal processing, machine learning, education and biology. He revels in the fact that you can apply a data-driven, algorithmic approach to the most challenging problems across any industry.

In 2018 Ahmad won the Reinforcement Learning Trading Challenge sponsored by the Brevan Howard Centre at Imperial College. The same year, he also won the Citadel 2018 UK Datathon and claimed two awards at Blackrock Algothon.

More recently, Ahmad interned at Brevan Howard as an AI Quantitative Researcher. He now fulfils the same role at Crypton, after being attracted by the exceptional team, growth and vision. At Crypton, Ahmad is applying the latest methods in machine learning to understand digital asset markets and execute trades on a smarter level than anyone else.


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