Zhi Deng
Engineering Leader at Plaid
New York City Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolZhi Deng is an engineering leader with nearly two decades of experience building and scaling consumer-facing applications, currently leading engineering at Plaid after a six-year leadership tenure at Instagram. He combines hands-on backend expertise—demonstrated by substantive contributions to the widely used pymatgen materials science library—with a track record of managing managers and distributed teams to deliver highly available experiences for top-ranked sites. Known for mentoring and growing the next generation of leaders, Zhi excels at aligning cross-functional stakeholders to turn business needs into reliable, production-grade systems. He brings deep operational rigor from roles at WebMD, WeWork, and others, and a practical curiosity for technical problem-solving that keeps him engaged across architecture, delivery, and developer productivity.
11 years of coding experience
23 years of employment as a software developer
High School Diploma, High School Diploma at Stuyvesant High SchoolBachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Stony Brook University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
lammps10
pymatgen10
science10
python10
materials-informatics10
computational-materials-science9
data-structures8
data-analysis8
data-structure8
Programming languages (5)
Github contributions (5)
materialsproject/pymatgen
Oct 2014 - Feb 2019
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 19 PRs, 5 pushes in 4 years 4 months
Contributions summary:Zhi primarily contributed to the `pymatgen` library, making enhancements and refactoring code related to materials analysis. Their work included smoothing arguments in the `DiffusionAnalyzer` class methods, which likely improved the usability or performance of diffusion analysis. Further contributions involved adding support for oxidation states in `LammpsData`, rewriting and improving the data handling logic for LAMMPS data files, and fixing potential bugs in Atoms section, demonstrating deep engagement with the library's core functionality for structure and data manipulation. Additionally, they made improvements to the XRD plot generation.
moleculespythonscienceelectronic-structurepowers
adengz/reactnd_flashcards
Jul 2020 - Jul 2020
A simple yet elegant, cross-platform flashcard mobile app built with React Native
Contributions:103 commits, 24 pushes, 1 branch in 7 days
reactbuilt-with-reactflashcardreact-nativeandroid
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