Peter Zhang
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AI and quantitative finance expert specializing in machine learning, reinforcement learning, and market game theory.
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Ph.D. candidate at the National University of Singapore, previously a visiting researcher at Yale University, focusing on market modeling and algorithm optimization.
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Proficient in Python, C++, and MATLAB, with expertise in data modeling, trading strategy development, and deep learning-based prediction. Conducts research on Graphon Mean-Field Games and the application of Transformers in financial markets.
My Story
Peter Zhang is a technology expert with extensive experience in machine learning, reinforcement learning, game theory, and quantitative finance. He is currently pursuing a Ph.D. at the National University of Singapore, specializing in multi-agent learning based on Transformers, market modeling, and optimization algorithms. He also conducted visiting research at Yale University, focusing on statistical learning and algorithm optimization.
Peter Zhang is proficient in Python, C++, and MATLAB, with deep expertise in financial market data modeling, quantitative trading strategy development, and deep learning-based prediction. His research covers market game theory (Graphon Mean-Field Games), time series forecasting, and machine learning algorithm optimization, which can be applied to developing efficient quantitative trading strategies.
Additionally, Peter Zhang has a profound understanding of the cryptocurrency market and has been a long-term investor in BTC, ETH, and other digital assets. By integrating AI research with trading strategies, he enhances strategy optimization and profitability. His technical expertise will contribute to Timeless Crypto in building a stable and efficient quantitative trading system, driving the team's innovation in market microstructure modeling, algorithmic trading, and AI-driven strategies.