Scholar
Artem Moskalev
Google Scholar ID: mh1CSCEAAAAJ
Johnson&Johnson
Citations & Impact
Citations
264
H-index
7
i10-index
6
Publications
20
Co-authors
11
list available
Publications
Resume (English only)
Academic Achievements
- Selected publications: 'HyperHELM: Hyperbolic Hierarchy Encoding for mRNA Language Modeling', 'Geometric Hyena Networks for Large-scale Equivariant Learning', 'InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference', 'HARMONY: A Multi-Representation Framework for RNA Property Prediction', 'HELM: Hierarchical Encoding for mRNA Language Modeling'.
Research Experience
- Currently a Research Scientist at Johnson&Johnson, working on reimagining drug discovery with AI.
Education
- PhD: University of Amsterdam, supervised by Prof. Arnold Smeulders and Prof. Erik Bekkers, focusing on geometric deep learning; MSc: Skolkovo Institute of Science and Technology, supervised by Prof. Anh-Huy Phan, working on high-dimensional convex optimization and inverse problems.
Background
- Research interests: geometric deep learning and language models, particularly in developing geometry-aware methods that efficiently learn from unlabeled data. Professional field: AI in drug discovery.
Miscellany
- Loves learning about cultures and history, enjoys folk and metal music, and in his free time, he likes playing chess and padel.
