Erik Cheng

San Francisco, California, United States

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Summary

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Senior

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Erik Cheng is a data scientist and computational chemist with nine years of experience applying atomistic simulations, machine-learned interatomic potentials, and statistical modeling to understand nonequilibrium surface chemistry and optimize plasma-mediated semiconductor processes. He holds a PhD in Materials Science and an MS in Statistics, and his PhD produced five first-author papers and awards from the American Vacuum Society for new mechanistic insights into atomic layer etching of silicon nitride. Erik combines deep first-principles expertise (DFT/DFTB/MD) with practical ML and HPC workflow development, and has translated that skillset into industry work including a recent role at Lam Research and an internship at Tokyo Electron US. He has contributed to educational open-source tooling—improving data visualization in the widely used Data 8 datascience library—and taught foundational data science at UC Berkeley, showing a knack for communicating complex methods to diverse audiences. Based in San Francisco, he balances rigorous research with applied engineering to move mechanistic understanding into scalable manufacturing solutions.

9 years of coding experience

10 years of employment as a software developer

Bachelor of Science (BS), Chemistry, Bachelor of Science (BS), Chemistry at University of California, Berkeley

Doctor of Philosophy - PhD, Materials Science, Doctor of Philosophy - PhD, Materials Science at The University of Texas at Austin

High School Diploma, High School Diploma at Cedar Falls High School

French, German, Chinese, English

Stackoverflow

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Github Skills (10)

data-visualizations10

pandas10

data-visualization10

data-visualisation10

python10

numpy9

datatable9

html-table9

jupyter-notebook9

datatables9

Programming languages (3)

TeXJavaScriptJupyter Notebook

Github contributions (5)

data-8/datascience

Feb 2017 - Feb 2017

A Python library for introductory data science

Role in this project:

Data Scientist

Contributions:12 commits, 3 PRs, 10 pushes in 9 days

Contributions summary:Erik primarily focused on enhancing the `datascience` library, particularly with features related to data visualization. Their commits demonstrate the implementation of color and size-based plotting capabilities within the `scatter` function. They addressed bugs to ensure compatibility with different data types and improved the library's functionality in generating plots. The user actively worked within the `test.ipynb` file to test the changes.

python-librarydata-analysispythonsciencedataframes

chengeaa/ispfinalproj

Dec 2019 - Jul 2022

Contributions:6 pushes, 1 branch in 2 years 8 months

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