Jiawei Zhuang
Research Intern at Google
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolJiawei Zhuang is a PhD candidate at Harvard and a research intern at Google who blends Earth science, high-performance computing, and machine learning to accelerate geospatial and differential-equation-driven modeling. With nine years of experience, he has built massively parallel implementations of GEOS-Chem and adapted its science codebase for multiple meteorological datasets, demonstrating both domain expertise and practical automation via Python. His work spans cloud-scale simulations, ML-accelerated solvers, and open-source Python tooling for reproducible geospatial workflows. Based in Zurich, he brings rigorous academic training (PhD/MS at Harvard, BS from Peking University) together with hands-on contributions to a widely used atmospheric chemistry model.
9 years of coding experience
Doctor of Philosophy - PhD, Engineering Sciences, 4.00/4.00, Doctor of Philosophy - PhD, Engineering Sciences, 4.00/4.00 at Harvard UniversityBachelor of Science - BS, Atmospheric Sciences and Meteorology, 3.84/4.00, Bachelor of Science - BS, Atmospheric Sciences and Meteorology, 3.84/4.00 at Peking University
English, Chinese, Japanese
Stackoverflow
181reputation
35kreached
1answer
0questions
Github Skills (9)
fortran10
atmospheric-modelling10
scientific-computing10
neural-network6
python6
scikit-learn6
bash4
script4
bash-shell4
Programming languages (11)
Github contributions (5)
geoschem/geos-chem
Jun 2017 - Aug 2018
GEOS-Chem "Science Codebase" repository. Contains GEOS-Chem science routines, run directory generation scripts, and interface code. This repository is used as a submodule within the GCClassic and GCHP wrappers, as well as in other modeling contexts (external ESMs).
Role in this project:
Back-end Developer
Back-end DeveloperContributions:19 commits, 1 PR, 29 comments in 1 year 2 months
Contributions summary:Jiawei primarily worked on the GEOS-Chem science codebase, focusing on adapting the code to work with different meteorological datasets (MERRA2, FLEXGRID). Their contributions involved modifying preprocessor directives and conditional statements to ensure compatibility. The user also implemented changes to infer grid sizes from resolution tags and added placeholders for FLEXGRID integration, demonstrating a focus on code adaptability and integration with meteorological data sources. Further modifications were done automatically via python scripts, indicating integration and automation.
awscodebasecontextsscienceatmospheric-modelling
JiaweiZhuang/cloud-gchp-paper
Oct 2019 - Mar 2020
Code to reproduce GCHP-on-cloud paper
Contributions:2 releases, 46 commits, 2 PRs in 5 months
gcpmahjongatscloudreproduce
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