Jorge Chan-lau
Financial Markets Advisor at Credit Research Initiative (CRI)
McLean, Virginia, United States
Summary
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Senior🎓
Top SchoolJorge Chan-lau is a quantitative economist and financial markets advisor with 11+ years applying agent-based modeling, machine learning and AI to systemic risk, asset pricing and macroprudential policy for advanced and emerging markets. He has led multidisciplinary teams at institutions like the IMF, CRI and A+3 ReMRI to build production-grade tools—from the BuDA bottom-up default platform to Python ML crisis predictors and Hugging Face sentiment indices—used in surveillance and policy design. His work blends rigorous academic training (Columbia, Georgia Tech) with operational impact, including a clique-percolation network method the IMF uses to identify systemically important jurisdictions and pricing/economic capital models for IFC’s MATCH program. Based in McLean, VA, he also trains central bank and supervisory teams across continents and has a track record of translating complex analytics into dashboards and policy-ready models. An engineer by first training, he brings a practical systems mindset to computational finance and nature-based carbon valuation projects.
10 years of coding experience
3 years of employment as a software developer
Master of Science - MS Analytics (Computational), Master of Science - MS Analytics (Computational) at Georgia Institute of TechnologyM.Phil. Ph.D. Finance and Economics, M.Phil. Ph.D. Finance and Economics at Columbia Business SchoolB.S. Civil and Structural Engineering, B.S. Civil and Structural Engineering at Pontificia Universidad Católica del Perú
Spanish, English, FrenchGithub contributions (5)
jchanlau/ML_resources
Jun 2019 - Jul 2021
Contributions:52 commits, 4 PRs, 49 pushes in 2 years 1 month
jchanlau/bike-sharing
Jan 2020 - Jan 2020
Bike sharing resources
Contributions:2 PRs, 22 pushes, 1 branch in 2 days
bikebike-sharingsharing
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