# Kai Yang

> Staff Software Engineer, Machine Learning at LinkedIn

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/kaiyang2

## Work Experience
### Staff Software Engineer, Machine Learning @ LinkedIn
Jan 2019 – Present | Sunnyvale, CA
- Optimized Sponsored Message delivery to increase revenue and improve advertiser ROI.
- Built learning content recommendation systems to help members advance their careers and stay competitive in the job market.

### Machine Learning Engineer @ Quora
Jan 2016 – Jan 2019 | San Francisco Bay Area
Built feed and digest ranking systems to increase user engagement.

### Postdoctoral Scholar @ Stanford University
Jan 2015 – Jan 2016 | Stanford
- Developed efficient sparse direct solvers and preconditioners for discretized partial differential equations (PDEs).
- Introduced a novel technique that improved the robustness and stability of hierarchical solvers for large, ill-conditioned linear systems.

### Research Assistant @ Penn State University, Department of Mathematics
Jan 2012 – Jan 2015
Modeling, discretization and parallel solvers of Fluid-Structure Interactions (FSI)
Analysis and Application of Multigrid methods

### Teaching Assistant @ Penn State University, Department of Mathematics
Jan 2010 – Jan 2015
Grader for Math 403, Math 436, fall 2010- spring 2011
Instructor for Math 021, fall 2012
Instructor for Math 022, fall 2014

### Summer Intern @ Sandia National Laboratories
Jan 2013 – Jan 2013
Develop and implement semi-implicit Smoothed Particle Hydrodynamics method for incompressible flow using Lammps and Trilinos


## Education
### PhD candidate in Mathematics, minor in Computational Science
Penn State University

### BS in Information and Computational Science
Jilin University


## Contact & Social
- LinkedIn: https://linkedin.com/in/kai-yang-26aaa647
- Portfolio: https://profiles.stanford.edu/kai-yang

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Source: https://flows.cv/kaiyang2
JSON Resume: https://flows.cv/kaiyang2/resume.json
Last updated: 2026-04-12