Stephan Zheng is a San Francisco–based founder and CEO with a decade of experience building AI agents that help co-invent the future. He previously led the AI Economist research team at Salesforce Research and holds a PhD from Caltech, with research internships at Google bridging deep learning for NLP and vision. An active contributor to the AI‑Economist open-source project, he has improved installation, documentation, and usability—work that reflects his focus on research-to-production transitions. His early quantitative work (including a C++ valuation tool for exotic derivatives) and years teaching physics and math give him an unusually deep mathematical and systems foundation for productizing advanced ML.
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
Role in this project:
ML Engineer
Contributions:39 reviews, 31 commits, 18 PRs in 1 year 9 months
Contributions summary:Stephan made modifications related to setting up and configuring the AI-Economist project, focusing on improving the installation process and project description. Contributions include updating the setup.py file to reflect the correct author names and project description. They also removed Colab notebooks from tutorials. These changes suggest involvement in project maintainability, documentation, and user experience for a machine learning research project.
Contributions:161 pushes, 1 branch in 5 years 3 months
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