Our founders, Marshall Chang, Cameron Fen and Duncan Wong are Brandeis University graduates of class 2016. Sharing strong passion for quantitative trading and machine learning, they started working on this project since September 2016.
Their inspiration came from Google DeepMind's AlphaGo project, which is a Deep Reinforcement Learning agent that beats human Go world champions. Go, as a game with complexity at a number more than the atom in the universe, is arguably as hard as or even harder than trading financial markets, which they believe is the next game to be solved with Artificial Intelligence.
Currently pursuing PhD in Economics in University of Michigan, Cameron leads research in economics and oversees machine learning operations for the research team. He has previously worked in the Philadelphia Federal Reserve for 2 years as research assistant, working on cutting-edge economics forecasting tools with leading researchers in the field.
Graduated with MS in Financial Engineering from Imperial College, Duncan has 4 years’ experience working in a high frequency trading firm, developing proprietary trading systems with Sharp Ratio over 4. He is the head of system and oversees operations for the company.
Graduated with MA in International Economics and Finance from Brandeis University International Business School, Marshall lead the team in developing our Deep Reinforcement Learning and Machine Learning infrastructure for quantitative trading and economics research. He has 6 years of experience trading Foreign Exchange markets and work experience in UBS Global Asset Management and ICBC International.