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Achievement: Pull Shark

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Achievement: Pull Shark

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SergeiNikolenko/README.md

Sergei Nikolenko

👋 Hi there! I’m a data scientist with 4 years of experience in ML and drug design. I’m looking for exciting projects in drug development where I can apply my skills and keep learning. I’d be thrilled to join your team!

🌐 Explore my projects | View my resume

🛠 Key Skills & Tech Stack

  • Cheminformatics & Molecular Modeling:
    RDKit, BioPython, ACE, Chemprop, OpenMM
    Molecular Dynamics & Docking: GROMACS, LAMMPS, AutoDock Vina
    Quantum Chemistry: MOPAC, ORCA, VASP

  • Machine Learning & Data Science:
    Frameworks: PyTorch, TensorFlow, scikit-learn, Transformers, Optuna, PyG, DGL
    Libraries: Pandas, NumPy, XGBoost, CatBoost, Dask

  • Programming & Automation:
    Python (primary), C++, Go – expertise in asynchronous programming, multiprocessing, and multithreading
    DevOps & Workflow Orchestration: Docker, Kubernetes, SLURM, Bash, Airflow, Dagster

💬 Professional Development & Community

  • Languages: Upper-Intermediate English, with international collaboration experience.
  • Kaggle Expert: Check my Kaggle profile

📈 GitHub Stats

SergeiNikolenko's GitHub stats

🌐 Get in Touch

I’m always open to discussions and collaborations on projects within medicinal chemistry, drug discovery, and data science.

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  1. LPCE LPCE Public

    The LPCE project is designed to purify and process PDB structures to extract and filter ligands and remove unwanted components such as water molecules and junk ligands.

    Jupyter Notebook

  2. fukui_index_prediction fukui_index_prediction Public

    This project develops a machine learning model using Chebyshev graph convolutions within a Kernel-based Attention Network (KAN) to accurately predict Fukui indices, which are essential for assessin…

    Jupyter Notebook

  3. ChemRar ChemRar Public

    The project aims to build and evaluate machine learning models for predicting the biological activity of molecules. Both graph neural networks (GCN, GAT, GIN) and the XGBoost model based on molecul…

    Jupyter Notebook

  4. ksitest ksitest Public

    The goal is to impute STR (Short Tandem Repeats) data from SNP (Single Nucleotide Polymorphisms) data for Holstein cows, which is critical in verifying the genetic relationship between animals for …

    Jupyter Notebook