Skip to content
View RemyLau's full-sized avatar
πŸ˜Άβ€πŸŒ«οΈ
πŸ˜Άβ€πŸŒ«οΈ

Highlights

  • Pro

Block or report RemyLau

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
RemyLau/README.md

Hi there πŸ‘‹

I am a Postdoctoral Fellow in the Ray and Stephanie Lane Computational Biology Department at Carnegie Mellon University. I currently work on developing computational and machine learning methods, as well as software, for analyzing and understanding single-cell epigenomics.

I obtained my Ph.D. degree in the Department of Computational Mathematics, Science & Engineering (CMSE) at Michigan State University. My training focused on network biology, graph representation learning, spectral graph theory, and machine learning.

Anurag's GitHub stats

πŸ›  I’m currently developing

  • Stay tuned! Something exciting is going online soon!

🧰 I'm actively maintaining several packages related to my past / recent projects

  • obnb [paper]: a Python toolkit for setting up benchmarking datasets using publicly available biomedical networks and gene annotation resources. A comprehensive benchmarking study with various graph neural networks and graph embedding methods is presented in obnbench.
  • DANCE [paper]: an extensive toolkit for deep learning with single-cell (multi-)omics data.
  • PecanPy [paper]: a memory efficient and Numba accelerated Python implementation of node2vec with an improved version node2vec+ [paper] for weighted graphs.
  • PyGenePlexus [paper]: a network-based gene classification service using machine learning and gene interaction network features.
  • GTaxoGym [paper]: a taxonomic study of benchmarking graph datasets from various domains based on the GNN model sensitivity to a collection of graph perturbations.

πŸ“« Find out more about my work and reach out to me

⚑ Side projects

  • ✍️ I share my passion about network biology and machine learning via blog posts on Medium
  • πŸ‘€ I create mathematical and algorithmic visualizations using Manim, which was first developed and used by my favorite math YouTube channel 3Blue1Brown.
  • πŸ€— I contribute to open source projects in various ways
  • πŸ“¦ I work on several small packages on the side to help improve my production workflow and exercise my dev workflow
    • pydab: a tool for working with dab files used by Sleipnir, a C++ library for machine learning on genomic data.
    • py2zenodo: a command line tool for uploading data to Zenodo
    • fastauroc: a Numba accelerated computation of the area under the receiver operating characteristic.

Installation notes

conda create -n remylau python=3.11 -y && conda activate remylau

pip install -e .

conda clean --all -y

Pinned Loading

  1. G-Taxonomy-Workgroup/GPSE G-Taxonomy-Workgroup/GPSE Public

    Graph Positional and Structural Encoder

    Python 43 3

  2. krishnanlab/obnb krishnanlab/obnb Public

    A Python toolkit for setting up benchmarking dataset using biomedical networks

    Python 21 1

  3. krishnanlab/PecanPy krishnanlab/PecanPy Public

    A fast, parallelized, memory efficient, and cache-optimized Python implementation of node2vec

    Python 157 22

  4. OmicsML/dance OmicsML/dance Public

    DANCE: a deep learning library and benchmark platform for single-cell analysis

    Python 353 36

  5. G-Taxonomy-Workgroup/GTaxoGym G-Taxonomy-Workgroup/GTaxoGym Public

    Taxonomy of Benchmarks in Graph Representation Learning

    Python 19

  6. krishnanlab/PyGenePlexus krishnanlab/PyGenePlexus Public

    A network based gene classification library to generate genome wide predictions about genes that are functionally similar to the input gene list.

    Python 20 3