Alexander Grigorievskiy
Lead AI Researcher at Comparables.ai
Espoo, Finland
Summary
👤
Senior🎓
Top SchoolAlexander Grigorievskiy is a Lead AI Researcher with 11 years of hands-on experience applying probabilistic and deep learning methods to production problems such as recommendation, NLP, federated learning and anomaly detection. He combines a PhD-level background in Gaussian Processes and fast-training neural models with practical delivery across industry—contributing code to prominent open-source projects like SciPy and GPy while shipping POCs and deployed LLM-based search and summarization at Comparables.ai. Comfortable translating complex math into plain language, he has led research directions and built toolboxes for vertical federated learning at Sber AI Lab and routinely bridges R&D, engineering and business via entrepreneurial training from EIT Digital. Colleagues rely on him for pragmatic, scalable solutions and for organizing small, efficient AI teams that move from prototype to production.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES, Doctor of Philosophy - PhD, COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES at Aalto UniversityDoctoral School, Business, Doctoral School, Business at EIT Digital AlumniMaster of Science (M.Sc.), Machine Learning and Data Mining, (with distinction), Master of Science (M.Sc.), Machine Learning and Data Mining, (with distinction) at Aalto-yliopistoLomonosov Moscow State University
English, Russian, Finnish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (17)
algorithms10
python10
testing10
machine-learning10
numpy10
gaussian-processes10
gpy10
lapack10
scientific-computing10
kernel-methods10
scipy9
mathematical9
linear-algebra9
modeling9
fortran8
Programming languages (4)
Github contributions (5)
SheffieldML/GPy
Mar 2015 - Jun 2017
Gaussian processes framework in python
Role in this project:
ML Engineer
ML EngineerContributions:33 commits, 5 PRs, 8 comments in 2 years 3 months
Contributions summary:Alexander primarily contributed to the implementation and testing of Gaussian Process (GP) kernels within the GPy framework. Their work focused on adding a standard periodic kernel, including its mathematical formulation and integration into the existing codebase. Further contributions involved writing tests for the periodic kernel and other SDE kernels, ensuring their functionality and correctness. The user also made modifications to existing kernels and added tests for SDE (Stochastic Differential Equation) representations of various kernels, including the Matern and RBF kernels.
gaussiangaussian-processespython
scipy/scipy
Jan 2015 - Mar 2015
SciPy library main repository
Role in this project:Back-end Developer
Back-end DeveloperContributions:14 commits, 5 PRs, 15 comments in 1 month
Contributions summary:Alexander primarily contributed to the SciPy library by adding wrappers for LAPACK least-squares solvers and the *lasd4 function. They implemented tests for the newly added functions and corrected existing bugs. Their work involved modifying and extending the existing LAPACK functionality within the SciPy ecosystem, improving the library's numerical capabilities.
scipypythonscientific-computing
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