Tianjian Qin

Tianjian

PhD candidate, theoretical biologist
I study systems biology by modeling and simulation. I am interested in phylogenetic comparative methods and parameter estimation approaches.

What I do

In my current project, I develop stochastic models to bridge theoretical and empirical studies at different phylogenetic scales. In my spare time, I try to bring data to life. Below is an overview of my skill sets, you can find out more in my blogs and projects.

R

Package development, data analysis, visualization, modeling, simulation.
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C, C++

Software development, integration with R/Python, modeling, simulation.
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Python

Machine learning with PyTorch, PyTorch Geometric, Sklearn, Tensorflow.
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HTML, CSS, JS

Web development, interactive data visualization with D3.js.

Bash, Server, HPC

Server-side software maintenance, HPC management.

TeX

Typesetting, rendering and visualization with LaTex, TikZ and PGFPlots.

GIS, Bioinformatics

Geospatial analysis, phylogeny reconstruction, metagenomics

Big Data Tools

Learning to use SQL, browser automation with Selenium, BeautifulSoup and Puppeteer.

Latest Blog Posts

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Sub-Species Level Diversification and Tree Coarsening

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Integrating Pre-Trained PyTorch Models into Your R Package

Pre-trained neural network models can significantly enhance your R projects. This tutorial will walk you through the process taking my R package EvoNN as an example...

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A Protocol to Bridge Phylogeny and GCN

Phylogenies are essentially graphs. Therefore, we can utilize a specific class of neural networks-the graph convolutional networks-to extract valuable information. But how? ...

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