Summary
Jianhua Huang is a Senior Staff Machine Learning Engineer with 11 years of experience building production-grade risk and fraud systems, currently leading advanced ML efforts at Block (Cash App). He combines a strong academic background in Earth and Atmospheric Modeling and machine learning with hands-on expertise across Python, R, Spark, TensorFlow, and cloud platforms to design scalable, real-time anomaly detection and model management pipelines. Jianhua has driven cross-functional programs from 0-to-1, led mitigation of multi-million-dollar fraud losses, and holds a patented offline risk management solution that removed over half of bad actors on the platform. He mentors engineers, scales hundreds of live models, and contributes practical open-source tooling—like streamlineR and a geospatial R Shiny app—demonstrating an unusual blend of spatial-statistical rigor and production ML engineering.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Earth and Atmospheric Modeling, Doctor of Philosophy (Ph.D.), Earth and Atmospheric Modeling at Arizona State University
Master’s Degree, Computer Science (Machine Learning), Master’s Degree, Computer Science (Machine Learning) at Georgia Institute of Technology
Earth and Atmospheric Modeling, Earth and Atmospheric Modeling at Purdue University
Bachelor's Degree, Economics, Bachelor's Degree, Economics at Shandong University
English, Chinese, Chinese