Summary
Lingling Zheng is a Principal Applied ML Scientist Lead with 12+ years of experience applying advanced statistical and machine learning methods to cloud systems, fraud detection, and biomedical research. She leads teams at Microsoft building AIOps/AIDevOps solutions for M365 and Azure, driving improvements in latency, availability, and LLM quality while authoring award-winning work on log intelligence and cloud failure prediction. With a PhD in Computational Biology & Bioinformatics and doctoral training in statistics and ML, she blends deep Bayesian-methods expertise (sparse factor analysis, MCMC, variational Bayes) with practical production engineering across global datacenters. Previously at Amazon she led credit card fraud prevention and NLP-driven automation that cut operational costs and uncovered emerging fraud from unlabeled social data. She is a hands-on leader and mentor who adapts coaching to business priorities and has a track record of translating complex research into measurable cost savings and robust, scalable systems. Coding as art, she pairs rigorous academic modeling with creative engineering to solve heterogeneous, high-dimensional data problems.
12 years of coding experience
9 years of employment as a software developer
PhD Computational Biology & Bioinformatics, PhD Computational Biology & Bioinformatics at Duke University
visiting student Bioinformatics Research Center,Prof. Zhao-Bang Zeng's research group, visiting student Bioinformatics Research Center,Prof. Zhao-Bang Zeng's research group at North Carolina State University
B.S Biotechnology, B.S Biotechnology at Zhejiang University