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KonNik88/README.md

Hi there

I’m Konstantin Nikiforov — MD, Molecular Geneticist (Russia) transitioning into Data Science & Machine Learning.
I like end-to-end work: data → features → models → APIs → simple UIs → orchestration.

Focus: applied ML for business (analytics & decision support), reproducible pipelines, model calibration & evaluation.
Interests: neural networks & AI, biomedical ML, causal inference, interpretable models, NLP/linguistics, music.

Stack

Core: Python · SQL · Pandas · NumPy · scikit-learn · CatBoost · XGBoost · LightGBM · Optuna
DL/NLP: PyTorch · Hugging Face · Sentence-BERT · (SimCLR/BYOL, Diffusion — exploring)
Recsys: ALS (implicit) · Hybrid SBERT+ALS+CatBoost · Qdrant (vector DB)
Time Series: Prophet · TBATS · ETNA/AutoTS · backtesting (rolling/holdout)
MLOps/App: FastAPI · Streamlit · Airflow · Docker/Compose · MLflow
Data & Scale: Spark (PySpark) · PostgreSQL · MySQL
XAI/Visualization: SHAP · LIME · Plotly/Dash · Matplotlib · ydata-profiling
Domains: Tabular ML · Recommenders · NLP · Time Series · BioML · CV

Exploring: Ray/Dask · GNNs · SSL

Selected Projects

  • Hybrid Book Recommender System — CatBoost + ALS + SBERT · FastAPI + Streamlit · Docker · Qdrant
    repo
  • BlendCAL — Conversion Prediction — CatBoost/XGBoost/LightGBM ensemble · FastAPI · Streamlit · Airflow DAGs · Docker Compose
    repo
  • Model Drift Monitoring — Evidently + SHAP + PSI/JS checks · alert policy demo
    repo
  • Panel Time-Series Forecasting — ARIMA, TBATS, Prophet, Darts · Optuna-tuned baselines
    repo
  • Omics Survival Analysis — RNA-seq PCA + embeddings for bioinformatics
    repo

Languages

English (B2) · French (B2)

Contact

Email: [email protected] · Telegram: @Konnik1988 · GitHub: https://github.com/KonNik88

TL;DR

MD molecular geneticist building practical DS/ML pipelines (Python, FastAPI, Streamlit, Airflow, Docker).

Popular repositories Loading

  1. omics-survival-embeddings omics-survival-embeddings Public

    Benchmarking embedding methods (UMAP, VAE, PCA, FA, ICA, etc.) for survival prediction on omics data with TabNet, CatBoost and ridge models.

    Jupyter Notebook 2

  2. blendcal-conversion-prediction blendcal-conversion-prediction Public

    End-to-end ML pipeline for predicting conversion in web sessions: feature engineering, CatBoost+XGBoost+LightGBM ensemble with calibration, FastAPI service, Streamlit UI, Airflow DAG orchestration,…

    Jupyter Notebook 1

  3. heart-disease-ml-practice heart-disease-ml-practice Public

    Practice notebook on heart-disease risk with a small/noisy dataset: EDA → preprocessing → classic ML baselines (scikit-learn). Not for clinical use

    Jupyter Notebook 1

  4. pca-genotypes-africa pca-genotypes-africa Public

    Genome-wide PCA analysis and clustering of African populations (Namib/Angola project, Oliveira et al. 2023)

    Jupyter Notebook 1

  5. pca-rnaseq-analysis pca-rnaseq-analysis Public

    PCA and UMAP analysis of bulk RNA-seq (HL-60, GSE184891) and scRNA-seq (AML, GSE116256). Includes QC, visualization, clustering, and biological interpretation.

    Jupyter Notebook 1

  6. pancreatic-disease-prediction-ml pancreatic-disease-prediction-ml Public

    Pancreatic disease prediction from biomarker tabular data (Debernardi et al., 2020) — EDA, classical ML (CatBoost/LightGBM/XGBoost), PyTorch MLP, LightAutoML, Optuna HPO, and rigorous evaluation

    Jupyter Notebook 1