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HFooladi/README.md

Hosein Fooladi

Machine Learning Researcher | Drug Discovery | Cheminformatics

PhD candidate at the University of Vienna, specializing in machine learning for drug discovery and out-of-distribution generalization. Interdisciplinary background spanning Biomedical Engineering (MSc, Sharif University) and Mechanical Engineering (BSc, Amirkabir University).

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What I Work On

  • High-performance scientific tooling in Rust (PDB/SDF parsers, molecular tokenizers)
  • Out-of-distribution generalization and robustness for molecular property and activity prediction
  • Graph neural networks for chemistry and drug discovery
  • Test-time training and domain adaptation in chemical space
  • Generative models for drug design (Diffusion, Flow-based models)

Featured Projects

Project Description
GNNs-For-Chemists Educational material: GNN implementations from scratch for chemists
pdbrust Rust library for parsing PDB files
ALineMol ML model performance on OOD data in chemistry
THEMAP Task hardness estimation for molecular activity prediction

GitHub Stats

GitHub stats

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  1. GNNs-For-Chemists GNNs-For-Chemists Public

    Implementations of different GNNs from scratch for chemists

    Jupyter Notebook 161 29

  2. pdbrust pdbrust Public

    A Rust library for parsing PDB (Protein Data Bank) files

    Rust 12 2

  3. THEMAP THEMAP Public

    Task Hardness Estimation for Molecular Activity Predcition (THEMAP)

    Jupyter Notebook 4 1

  4. ALineMol ALineMol Public

    Exploring performance of machine learning model on out-of-distribution data in chemical domain

    Jupyter Notebook 5

  5. molax molax Public

    Molecular active learning with JAX

    Python 1

  6. Self_Organization Self_Organization Public

    Mathematical Model For Self-Organization of Human Embryonic Stem Cells

    Jupyter Notebook 3 2