Peter Chen

Professor at AMS China Business Consulting Company Ltd.

Xuhui District, Shanghai, China
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Summary

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Senior
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Top School
Peter Chen is a seasoned professor and business consultant with over four decades of hands-on leadership across corporate management, international joint ventures, and executive training. He teaches English-language courses at East China Normal University on China as an emerging market, business culture, and international trade, drawing on prior VP and general manager roles that built and operated cross-border ventures. A specialist in administrative excellence, time and information management, and shorthand-based transcription, he now coaches executives and administrative staff to improve decision-making and operational efficiency. He also leads management consulting engagements that implement lean practices, 6S, and restructuring to revive struggling manufacturers. Unusually for an educator, he combines deep practical top-management experience with a shorthand skillset that enables rapid, accurate capture of executive knowledge. Based in Shanghai, he bridges Western academic training (B.A./M.A. from San Francisco State) with decades of China-focused business practice.
code8 years of coding experience
job7 years of employment as a software developer
bookB.A., M.A. Business Administration, Marketing, Accounting and Business Education, B.A., M.A. Business Administration, Marketing, Accounting and Business Education at San Franisco State University
bookCertificate of Higher Vocational Education, Commercial Vocational Education with Major in Secretarial Science, Certificate of Higher Vocational Education, Commercial Vocational Education with Major in Secretarial Science at Bangkok Commercial College
languagesChinese, Thai, English
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Github Skills (4)

machine-learning10
reinforcement-learning10
julia10
deep-reinforcement-learning10

Programming languages (2)

JuliaPython

Github contributions (5)

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A reinforcement learning package for Julia
Role in this project:
userBack-end Developer & ML Engineer
Contributions:7 reviews, 18 commits, 25 PRs in 2 months
Contributions summary:Peter primarily contributed to the reinforcement learning package for Julia, implementing and testing core functionalities. Their work included adding equality and hash methods for the `AbstractEnv` interface, along with tests for the `KuhnPokerEnv`. They also implemented a `weighted_softmax_explorer` and supplemented the `BehaviorCloningPolicy` with new methods. Further contributions included implementing and experimenting with the NFSP algorithm and the MADDPG algorithm.
reinforcement-learningstatistical-learningdeep-reinforcement-learningmachine-learningjulia
A reinforcement learning package for Julia
Contributions:157 pushes, 37 branches in 6 months
reinforcement-learningreinforcementjulia
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