Tingzheng Hou
Graduate Student Researcher
Berkeley, California, United States
Summary
🎓
Top SchoolTingzheng Hou is a PhD candidate and graduate student researcher at UC Berkeley with eight years of experience bridging materials science and scientific software engineering. Trained at Tsinghua (BEng, M.S.) and now pursuing a PhD in Materials Science, he combines deep domain expertise in materials and chemical engineering with hands-on back-end development—contributing to the widely used pymatgen project by improving LAMMPS I/O, data parsing, and structure export robustness. Based in Berkeley, he is actively exploring roles in finance, programming, marketing, and consulting beginning summer 2021, bringing a quantitative mindset and interdisciplinary curiosity. Known for refactoring complex code paths and clarifying documentation, he excels at translating research-grade models and data into reliable, production-ready tools.
7 years of coding experience
Doctor of Philosophy (PhD), Materials Science, Doctor of Philosophy (PhD), Materials Science at University of California, BerkeleyBachelor of Engineering (BEng), Materials Science, Bachelor of Engineering (BEng), Materials Science at Tsinghua University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
lammps10
pandas10
python10
materials-informatics9
data-analysis9
science9
data-structures8
data-structure8
Programming languages (3)
Github contributions (5)
materialsproject/pymatgen
Mar 2019 - Aug 2021
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:1 review, 45 commits, 6 PRs in 2 years 6 months
Contributions summary:Tingzheng primarily contributed to the `pymatgen/io/lammps` module, modifying the `data.py` file extensively. They focused on refactoring the code, enhancing the string representation, and improving data handling, specifically concerning force field and topology information. Their work included changes to the structure export functionality and data file parsing, with a focus on addressing inconsistencies and supporting combined data objects. The user also made updates to the documentation.
moleculespythonscienceelectronic-structurepowers
htz1992213/pymatgen-1
Mar 2019 - Dec 2021
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.
Contributions:51 pushes, 1 comment in 2 years 9 months
moleculespythonrepresentationselectronic-structuregenomics
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