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kirilklein/README.md

Kiril Klein

Machine Learning Engineer · Causal Inference & Clinical NLP · PhD

LinkedIn Google Scholar Email

I build ML systems for clinical data: transformers pre-trained on longitudinal electronic health records, clinical NLP pipelines, and causal-inference methods for estimating treatment effects from observational data. PhD in Machine Learning and Causal Inference, University of Copenhagen.

Work

Aiomic (Copenhagen) — building the product ML stack from scratch: transformers combined with classical NLP/ML in a single pipeline, from data preparation and training through validation to Docker-based services and CI/CD.

PhD, University of Copenhagen — Scalable Causal Inference on Electronic Health Records Using Transformers. Pre-training transformers on structured longitudinal EHR and using them for outcome prediction and treatment-effect estimation.

Currently — maintaining CausalEstimate and contributing treatment-effect fixes to statsmodels.

Selected publications

CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
PMLR vol. 252 (MLHC), 2024. Joint first author.

MEDS — An Emerging Data Standard and Ecosystem for Health AI Research
NEJM AI, 2026. Co-author. (website · GitHub org)

BONSAI: A framework for processing and analysing Electronic Health Records (EHR) data using transformer-based models
Journal of Open Source Software, 2025. Co-author.

Full list on Google Scholar.

Python · PyTorch / Lightning · Hydra · scikit-learn · Dask · Docker · Azure · GitHub Actions

Some professional work lives under my work account, @kvk-cmd.

Pinned Loading

  1. causal-sandbox causal-sandbox Public

    Learn causal inference by changing the world. Guided lessons and a sandbox with confounders, mediators, colliders, and six estimators, live in the browser

    JavaScript

  2. FGA-DIKU/BONSAI FGA-DIKU/BONSAI Public

    A BERT-based framework for processing and analyzing Electronic Health Records (EHR) data. It provides an end-to-end pipeline for data preprocessing, model training, and clinical outcome prediction.

    Python 11 6

  3. mikkelfo/CORE-BEHRT mikkelfo/CORE-BEHRT Public

    Jupyter Notebook 19 5

  4. CausalEstimate CausalEstimate Public

    Lightweight causal inference from precomputed propensity scores and outcome predictions: IPW, AIPW, TMLE, matching, bootstrap CIs. Pandas-native.

    Python 2 2

  5. bonsai-causal bonsai-causal Public

    BONSAI Causal: transformer (ModernBERT) pipeline for EHR data in MEDS format, extended for causal inference — cohort matching, joint exposure/outcome finetuning, calibration, IPW/AIPW/TMLE effect e…

    Python 2 2

  6. mergeprint mergeprint Public

    A privacy-first, interactive one-page dashboard of your year on GitHub

    HTML