About Stefan Jansen
Financial machine learning, written by a practitioner who has taken research from data and labels through validation, trading systems, and live operation.
Stefan Jansen
Author, Applied AI founder, and financial ML practitioner
Stefan Jansen is the author of Machine Learning for Trading and the founder of Applied AI. His work in markets began on the investment side: he created Infusive Intelligence's New York office, built its investment data-science team and research platform, designed quantamental workflows and event forecasts, and served on the investment committee. Through Applied AI, he has continued to build quantitative research and live trading systems across equities and digital assets.
That experience shapes ML4T's focus on the complete workflow. The third edition and its companion software cover data, labels, validation, backtests, portfolio construction, costs, diagnostics, and live operation. The main repository has over 21K GitHub stars.
Background
- Author, Machine Learning for Trading (1st, 2nd, and 3rd editions)
- Founder of Applied AI, established in late 2015
- Investment data science, quantitative research, and live trading systems
- Harvard master's in economics and public policy; Georgia Tech MS in computer science; CFA charter
Written from the working process
A model forecast is only one step in a trading workflow. The harder questions are usually around data timing, label design, validation, costs, portfolio construction, monitoring, and the decision to stop, retrain, or deploy.
That is the practical center of ML4T. The third edition follows the path from research idea to evidence and then to live operation, with case studies across ETFs, crypto perpetuals, microstructure, options, futures, FX, firm characteristics, and US equities.
Stefan's production work also extends beyond markets to contract intelligence, healthcare forecasting, customer-lifecycle systems, and agent workflows. The domains differ, but the standard is the same: define what the system must do, evaluate it against that requirement, and build the operating process around it.
Working on implementation?
Applied AI is Stefan's consulting practice for teams building production AI and machine-learning systems: strategy, architecture, code, evaluation, and operation.