I am currently a Postdoctoral Researcher at the
Centre for Computational Biology (CBIO)
at
Mines Paris PSL
and
Insitut Curie.
I work under the supervision of
Chloé-Agathe Azencott,
Pierre Baduel,
and
Vincent Colot
on statistical machine learning for the integration of transposable elements variability and epivariability in genotype-to-phenotype studies.
Previously, I have been a PhD Student in Machine Learning at
DaSciM team
at
École Polytechnique,
under the supervision of
Jesse Read.
My research interests include:
- Machine Learning
- Genetics & Epigenetics
- Genotype-to-phenotype studies, GWAS
- Transposable elements & DNA methylation
My CV is available here.
I am currently a Postdoctoral Researcher at the Centre for Computational Biology (CBIO) at Mines Paris PSL and Insitut Curie. I work under the supervision of Chloé-Agathe Azencott, Pierre Baduel, and Vincent Colot on statistical machine learning for the integration of transposable elements variability and epivariability in genotype-to-phenotype studies. Previously, I have been a PhD Student in Machine Learning at DaSciM team at École Polytechnique, under the supervision of Jesse Read.
My research interests include:
My CV is available here.
Publications
- Antonenko E., Carreño A., Read J., Autoreplicative Random Forests for missing value imputation. Machine Learning journal (ECML/PKDD 2024 Journal Track), Volume 113, pages 7617–7643, (2024).
- Antonenko E., Mechenich M., Beigaitė R., Žliobaitė I., Read J., Backward inference in probabilistic Regressor Chains with distributional constraints. Advances in Intelligent Data Analysis XXII - 22nd International Symposium, IDA 2024.
- Antonenko E., Multi-target learning and prediction: novel methods and applications. PhD Thesis, 2023.
- Antonenko E., Read J., Chains of Autoreplicative Random Forests for missing value imputation in high-dimensional datasets. ArXiv pre-print, 2023.
- Antonenko E., Read J., Multi-modal Ensembles of Regressor Chains for multi-output prediction. Advances in Intelligent Data Analysis XX - 20th International Symposium, IDA 2022.
- Ivanenko V., Antonenko E. , Gelfand M., Yager J., Ferrari F., Changes in segmentation and setation along the anterior/posterior axis of the homonomous trunk limbs of a remipede (Crustacea, Arthropoda). PeerJ, 2016.
Talks and Posters
- July 25, 2023.
[Poster]
Genotype Imputation with Multi-label Random Forests.
ISMB/ECCB 2023, MLCSB Cosi, Lyon (France).
- May 26, 2023.
[Talk]
Multi-output machine learning with applications to genomics.
Institut Imagine, Paris (France).
- February 13, 2023.
[Talk]
Autoreplicative Random Forests for missing value imputation.
Group seminar, KU Leuven KULAK, Kortrijk (Belgium).
- November 21-22, 2022.
[Poster]
Genotype Imputation with Multi-label Random Forests.
MLCB 2022, virtual.
- September 19, 2022.
[Talk, Best paper award]
Chains of Autoreplicative Random Forests for missing value imputation in high-dimensional datasets.
Multi-Label Learning Workshop, current trends and open challenges, ECML PKDD 2022, Grenoble (France).
- April 21, 2022.
[Talk]
Multi-Modal Ensembles of Regressor Chains for Multi-Output Prediction.
IDA 2022, Rennes (France).
Teaching
- March, 2025 and 2024: Lecture on Introduction to large-scale ML & optimization. LSML: Large-Scale Machine Learning & Data Mining at École des Mines.
- December, 2023: Teaching assistant. Apprentissage artificiel (Machine Learning) at École des Mines.
- Spring, 2023 and 2022: Teaching assistant. CSE204: Machine Learning at École Polytechnique.
Reviewing
- Conference reviewer: ECML PKDD Research Track (2025, 2024), MLCB (2024, 2023).
- Journal reviewer: Machine Learning, Data Mining and Knowledge Discovery.