Principal Applied Scientist · Generative AI & Machine Learning
San Francisco Bay Area, California
I build AI systems across language, vision, and time series, bringing mathematical rigor to practical machine learning. My background spans Microsoft, Apple, Samsung, and academic research in nonlinear analysis and partial differential equations.
Email: jinghuayao AT gmail DOT com
Personal website · Publications · Résumé
- Generative AI: LLM agent workflows, multimodal understanding, distributed LLM/VLM fine-tuning, embeddings, and evaluation.
- Applied ML: forecasting, anomaly detection, NLP, computer vision, and operational automation.
- Mathematical foundations: nonlinear analysis, variational methods, PDEs, and dynamical systems.
- Microsoft — Principal Applied Scientist, Jul 2025–present.
- Apple — Senior Machine Learning Engineer, May 2020–Jun 2025.
- Samsung Display American Lab — Staff Machine Learning Engineer, Mar 2019–May 2020.
- Previously: Visiting Assistant Professor at the University of Iowa and Research Scholar at Kent State University.
- Ph.D. in Mathematics, Indiana University Bloomington, 2013.
Author or coauthor of 18 journal publications in nonlinear analysis and related areas. Selected work:
- Patterns of complex oscillations and instability in chemical reactions, Communications in Mathematical Sciences, 2019.
- Spectrum and bifurcation for semilinear elliptic problems in ℝᴺ, Journal of Differential Equations, 2017.
- O(2)-Hopf bifurcation for a model of cellular shock instability, Physica D, 2014.
At Apple, I was a main contributor to a series of 32+ one-hour ML/AI lectures in 2021–2022.
Interested in applied science and AI/ML opportunities, research collaboration, and thoughtful technical conversations. Reach me at jinghuayao AT gmail DOT com.
Personal profile; views are my own and do not represent my employers.