Introduction of the Third Domain Expert Candidate — Liang Wu

Since the Domain Expert Election Month, EpiK Protocol has announced two domain expert candidates — — Dr. Yu and Ms. Becky. If you want to review their introduction, click follow links:

Introduction of the first domain expert candidate

Introduction of the second domain expert candidate

This time, EpiK Protocol will introduce the third domain expert candidate — — Professor, Liang Wu.

Professor Wu, the expert in field of artificial intelligence and finance, as well as Professor of Finance in Sichuan University and a PhD at Brown University, has published many papers about machine learning and artificial neural networks in top journals such as ICPR, ICANN, Neurocomputing. Professor Wu was engaged in hedge fund and as the director of derivatives quantitative trading department for 5 years, leading his team to develop AI algorithms to find the best mutual funds for FOF to invest.

In the EpiK Protocol ecosystem, Wu will lead the EpiK community to build a mutual fund knowledge graph, including but not limited to collecting cross-sectional differences, product details, fund strategies, management methods, historical performance, fund manager profiles, etc. of existing mutual funds. Using AI technology to extract the behavior types of market participants, the balance of power formed by various games, and the analysis of breaking the effective breakthrough points under different game states in the market, etc., to solve the problems and pain points that are prone to financial big data based on time series in the quantitative transaction process to help users quickly make more reasonable investment decisions in terms of prices, macro indexes and market indexes when trading, and make effective predictions for the future market.

At the same time, with utilization of the mass unstructured information, map information into structured and standardized knowledge graphs and transaction models, complete in-depth analysis of relevant laws of capital market fluctuations, provided technology support and accurate and reliable data sources for public opinion monitoring, risk prediction, application decision-making, etc.

I believe that with the join of Professor Wu, an academic university, it will bring a different professional perspective and resources to EpiK Protocol ecosystem.