Summary
Alan King is a quantitative computing expert with 22 years of experience applying stochastic optimization, high-performance computing, and deep learning to finance, insurance, and production-inventory problems. He led research and development teams at IBM and spent decades at IBM TJ Watson Research Center building massively parallel solutions for options pricing, asset-liability management, and multi-period stochastic programs. A PhD in Applied Mathematics from the University of Washington, he mentors PhD-level researchers and bridges rigorous modeling with production-grade systems engineering. He also explored decentralized finance and continues to consult through his Ars Probabilitas venture, bringing uncommon fluency in both mathematical modeling and scalable implementation.
22 years of coding experience
5 years of employment as a software developer
PhD, Applied Mathematics, PhD, Applied Mathematics at University of Washington