Stephan Zheng is a founder and CEO based in San Francisco who builds AI agents to "co-invent" the future, drawing on 11 years of experience at the intersection of machine learning research and product. He led the AI Economist team at Salesforce Research and contributed to the well-known ai-economist framework, marrying reinforcement learning with socio-economic modeling. Trained as a theoretical physicist with a PhD from Caltech and advanced math at Cambridge, he brings a rigorous, quantitative mindset to applied AI. His background includes deep learning research stints at Google and hands-on engineering in finance, reflecting a rare blend of theory, production ML, and domain breadth.
11 years of coding experience
6 years of employment as a software developer
MASt (Cantab) Mathematics, MASt (Cantab) Mathematics at University of Cambridge
California Institute of Technology
Physics Mathematics, Physics Mathematics at Harvard University
MSc Theoretical Physics, MSc Theoretical Physics at Utrecht University
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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