Gleb Tikhonov
Academy Research Fellow at University of Helsinki
Espoo, Finland
Summary
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Senior🎓
Top SchoolGleb Tikhonov is an Academy Research Fellow and applied probabilistic machine learning expert with over a decade of experience building GPU-accelerated statistical software and scalable pipelines for biodiversity and geospatial AI. With a PhD in Statistical Biology from the University of Helsinki and an MSc in Applied Mathematics from MSU, he develops interpretable models that combine deep neural networks and Gaussian processes for longitudinal and multi-outcome problems. He has led academic projects from doctoral work through postdoctoral roles at Aalto and visiting research at Duke, and is the author of 30+ highly cited papers bridging theory and real-world ecological and biomedical applications. Comfortable with systems and competitive programming, he pairs strong implementation skills with stakeholder-facing collaboration and meticulous project management. An underappreciated strength is his track record of translating cutting-edge numerical GP techniques into practical, scalable tools for community and species‑level inference.
10 years of coding experience
7 years of employment as a software developer
High School, Mathematics and Computer Science, Excellent, High School, Mathematics and Computer Science, Excellent at Moscow High School №2Doctor of Philosophy - PhD, Statistical Biology, Doctor of Philosophy - PhD, Statistical Biology at University of HelsinkiLomonosov Moscow State University
Russian, English, Finnish
Github Skills (31)
hierarchical9
r-package9
meta-analysis9
tidymodels9
numerical-analysis9
bayesian-methods9
structured-data8
python8
regression8
analytical8
probabilistic8
machine-learning8
statistics8
probabilistic-reasoning8
probabilistic-programming8
Programming languages (3)
Github contributions (5)
belg92/HMSC
Feb 2018 - Mar 2019
Hierarchical Model of Species Communities (HMSC) is an R package, which provides extensive set of analytical tools devised for numerical analysis of data on ecological communities or other similarly structured data. The methodological core of the HMSC approach is centered on combination of hierarchical regression and latent factor models.
Contributions:121 commits, 104 pushes, 12 branches in 1 year
hierarchical-modelhierarchicalr-packagefactorcommunities
gtikhonov/HMSC-Matlab-BigSpatial
Oct 2018 - Dec 2019
Contributions:5 commits, 3 pushes, 1 branch in 1 year 1 month
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