Scholar
Stas Syrota
Google Scholar ID: 5IfafFYAAAAJ
PhD researcher at Technical University of Denmark
Citations & Impact
Citations
6
H-index
1
i10-index
0
Publications
2
Co-authors
5
list available
Publications
Resume (English only)
Research Experience
- Before pursuing his PhD, worked as a Machine Learning Engineer (recommender systems) and as a Data Scientist.
Education
- PhD: Technical University of Denmark (DTU), supervised by Søren Hauberg; Master's: Technical University of Denmark (DTU), Mathematical Modeling and Computing; Bachelor's: University of Copenhagen (KU), Mathematics-Economics. In between the degrees, took a semester of a Statistics Master’s program at KU to study stochastic processes.
Background
- Research interests: intersection of geometry, statistics, and machine learning, particularly in the context of deep generative models. Focused on understanding the identifiability of latent variable models and the generalization properties of deep neural networks, with a strong emphasis on geometric approaches and Bayesian methods. Excited about applying machine learning to real-world problems, especially in fields that require a geometric understanding of data or where uncertainty quantification is crucial.
