Xiaozhou Zou is a Principal Data Scientist based in Worcester, MA with nine years of industry experience and a strong academic foundation in computational mathematics and data science. He combines hands-on expertise in deep learning, surrogate modeling, and AI-assisted equipment design with production skills across Spark, Hadoop, Kafka, NoSQL, and AWS to move research into deployable systems. At Aspen Technology he progressed from developing ML packages and document-to-knowledge-graph CV pipelines to leading research teams, designing roadmaps, and shipping cross-functional pilot demos. His research contributions include accelerating GAN convergence with a multi-phase training scheme and inventing an advanced sampling method that improved model training speed and accuracy. Comfortable across Python, Scala, Java, and visualization stacks, he pairs mathematical rigor with practical engineering to tackle domain-specific challenges in chemical engineering and industrial AI.
9 years of coding experience
6 years of employment as a software developer
Master’s Degree Data Science, Master’s Degree Data Science at Worcester Polytechnic Institute
Bachelor’s Degree Computational Mathematics, Bachelor’s Degree Computational Mathematics at Zhejiang University
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