Dr. Yves J. Hilpisch

About

Quant technologist integrating finance, AI, and automation.

I blend academic rigor with production-grade execution to empower finance professionals transitioning into an AI-first era.

With a Ph.D. in Mathematical Finance, I lead The Python Quants and The AI Machine, focusing on algorithmic trading, Python-driven analytics, and enterprise AI adoption. My work bridges research and industry impact through books, programs, and advisor roles.

Today, I partner with institutions and practitioners to build AI-native workflows: from LLM-assisted research pipelines to quantitative trading systems. My teams deliver portfolio-ready education, code assets, and community programs that help quants stay ahead.

Initiatives & Roles

Hands-on programs, products, and communities for AI and finance innovators.

Explore the ecosystem powering Python, quantitative finance, and generative AI adoption worldwide.

🧮 The Python Quants

Founder & CEO delivering quantitative finance training and tooling for modern quants.

Visit TPQ ↗

🧠 The AI Engineer

Flagship training program for AI-native builders. Ship production LLM systems with hands-on capstones.

Join TAE ↗

🎓 CPF Program

Director of the Certificate in Python for Finance — 400+ hours of code, video, and projects.

Learn about CPF ↗

🤖 The AI Machine

Advanced secure communication solutions (e.g. MagicCap for encrypted ephemeral chat).

Discover TAIM ↗

📚 Publications

Author of ten books on Python, quantitative finance, and applied machine learning for markets.

View catalog ↗

▶️ Content & Media

Creating instructional video series and AI-powered podcasts for the quant community.

Watch on YouTube ↗

🏛 Academic Partner

Lecturer at CQF and EPAT programs, bringing advanced Python and AI workflows to practitioners.

CQF insights ↗

🌐 Quant Communities

Organizing meetups in London, New York, and beyond to grow the Python for finance network.

Join meetups ↗

💡 quants@dev

Leading developer community initiatives that align quant engineering with AI-native practices.

Explore community ↗

📦 DX Analytics

Author of the DX Analytics Python package for valuation, risk analytics, and derivatives pricing.

Access GitHub ↗

AI-Powered Discussion Papers

Exploring the frontiers of human progress — from AI to longevity to quant finance.

Rapidly developed with GenAI tooling, these papers capture key theses and frameworks driving myself, humanity in general, and our programs in particular.

Deep Q-Life: Markov, Bellman, and Habits

Recasts everyday habit building as a compact reinforcement learning problem. Using the MDP lens and the Bellman principle — choose what is good now and sets up good options next — Deep Q-Learning provides a simple loop: try, remember what worked, and refine with weekly reviews. Includes relatable examples and checklists for practical, improvable policies.

Longevity and Health: From Myths to Proven Protocols

Synthesizes the strongest human evidence for extending healthspan: a Mediterranean-style, protein- and fiber-rich diet, structured aerobic (including Zone 2) and resistance training, 7-9 hours of sleep, and intentional hydration. Completes the protocol with stress-regulation practices and social connection to counter the mortality impact of chronic isolation.