Aspiring undergraduate student interested in physics, scientific computing, and data-driven research.
I am currently building independent research-oriented projects using real scientific datasets. My current featured project uses Gaia DR3 and LAMOST data to explore chemo-dynamical structures of Milky Way stellar populations.
- Physics and Astrophysics
- Scientific Computing
- Data Analysis
- Machine Learning for Scientific Data
- Astronomical Survey Data
- Research Software Development
An umbrella research-oriented project exploring Milky Way stellar populations using Gaia DR3 astrometry and LAMOST spectroscopy.
The project is organized into three connected sub-projects:
-
Gaia–LAMOST Cross-matching and Chemo-kinematic Feature Construction
Building a clean Gaia–LAMOST cross-matched sample and constructing analysis-ready features. -
Unsupervised Stellar Population Discovery
Using visualization, dimensionality reduction, and clustering methods to explore possible stellar population structures. -
Interpretable Machine Learning for Galactic Substructure Candidates
Developing interpretable workflows for identifying and analyzing candidate Galactic substructures.
Current progress:
- Gaia DR3 sample query and validation
- LAMOST catalogue exploration and cross-match
- Chemo-kinematic feature construction
- Exploratory visualization
- Dimensionality reduction and clustering
- Candidate selection workflow
- Research-style project report
Repository: gaia-lamost-galactic-archaeology
Medical simulation software project with interactive 3D visualization and research-oriented workflow design.
Independent scientific computing project using large-scale astronomical survey data.
Python · NumPy · Pandas · Matplotlib · Scikit-learn · Jupyter · Git
Currently learning and using:
Astropy · ADQL · Scientific Visualization · Research Workflows
Also experienced with:
React · TypeScript · Three.js · Simulation Systems
- Website: https://lior-linho.github.io/
- GitHub: https://github.com/lior-linho
- LinkedIn: https://www.linkedin.com/in/lior-l-05b4322a7
- ORCID: Coming soon