Summary
Sorawit Saengkyongam is a research scientist based in Zürich with a decade of experience at the nexus of causality, invariance, and robust machine learning, currently applying these strengths to AI for Health at Apple. He combines rigorous academic training (PhD-level statistics from ETH Zürich and an MSc in Machine Learning from UCL) with applied impact, having driven personalization systems at Agoda that produced multi-million dollar gains and led causal representation work at Carnegie Mellon and Harvard. His research spans high-dimensional observational problems—from satellite time-series for aerosol–cloud interactions to mobile health interventions—emphasizing methods that remain reliable under distribution shift. Known for bridging theory and production, he has a track record of translating causal ML advances into deployed health technologies that tolerate real-world variability.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at ETH Zürich
Bachelor’s Degree, Statistics, 1st Class Honours, Bachelor’s Degree, Statistics, 1st Class Honours at Chulalongkorn University
University College London
English, Thai