Summary

Quantitative Developer at Scalable Ph.D. Candidate at LMU Munich

Education

• Mathematics in Data Science

  2024-07
  Technical University of Munich

  Courses: DAAD Master Scholarship for academic performance and research potential
• System Analysis

  2021-06
  Igor Sikorsky Kyiv Polytechnic Institute

  Courses: Merit-based scholarship for academic excellence (top 15% of students)

Work Experience

• Quantitative Developer

  2024-01 - Current
  Worked on optimization, risk modeling, and ML models for trading execution.
• Ph.D. Candidate in Statistics

  2026-03 - Current
  Ph.D. research in uncertainty quantification and probabilistic machine learning.

  • Supervisor: Professor David Rugamer.
  • Lab website: https://www.muniq.ai/

Publications

• Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models

  2026
  Submitted to ICML

  Authors: Maksym Tretiakov, Sarah Filippi, Vincent Fortuin, Ruth Misener, Ruby Sedgwick, James Odgers.

  View Publication
• PAC Bayes Bounds Evaluation Framework

  2025
  Authors: Yauheni Mardan, Maksym Tretiakov, Alexander Immer, Vincent Fortuin.

  View Publication
• A new atlas to study embryonic cell types in Xenopus

  2024
  Developmental Biology Journal

  Authors: Kseniya Petrova, Maksym Tretiakov, Aleksandr Kotov, Anne H. Monsoro-Burq, Leonid Peshkin.

  View Publication

Languages

• English

  Fluent
• Ukrainian

  Native