February 2026 - Released Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets paper, accepted to EACL 2026 MME!

January 2026 - Very honored to be included in the Forbes Ukraine's Top 20 AI Leaders in Ukraine list!

December 2025 - I have joined ETH AI Center as a Research Engineer to work on post-training for the next versions of Apertus open model as part of Swiss AI Initiative!

November 2025 - Presented a lecture on adapting LLMs to EEU languages at the Lviv Polytechnic University Data Science Club.

October 2025 - Presented our work on multilingual models for EEU languages at the GIST workshop in Geneva.

September 2025 - Released MamayLM v1.0 Ukrainian-focused multimodal LLM.

July 2025 - Joined Hugging Face as a Machine Learning Research Engineer Intern to work on data science coding agents.

May 2025 - Finished my master thesis under the supervision of prof. Vechev and released a resulting Ukrainian-focused MamayLM v0.1 model.

October 2024 - Our paper A Synthetic Dataset for Private Attribute Inference has been accepted to NeurIPS 2024 Datasets and Benchmarks Track.

Post-training (SFT), multilinguality and alignment for Apertus model series

◆ Improving data sourcing and training methods for data science coding agents
◆ Testing multi-node multilingual training

◆ Research Assistant at Secure, Reliable, and Intelligent Systems Lab (SRI)
◆ Improving multilingual training, alignment and safety for EEU languages

◆ Project Intern at Secure, Reliable, and Intelligent Systems Lab (SRI)
◆ Documenting capabilities and vulnerabilities of the state-of-the-art large language models
◆ Contributing to LVE (Language Model Vulnerabilities and Exposures) project
◆ SynthPAI: A Synthetic Dataset for Personal Attribute Inference: Semester project under supervision of Prof. Martin Vechev (co-supervised by Robin Staab and Mark Vero)

◆ Went through a 3-month internship with intensive training for statistics, machine learning techniques, data engineering and cloud (Azure)
◆ Executed an end-to-end Market Mix Modelling project for a particular segment of one of the world's biggest CPG companies, including methods research, EDA, developing a statistical model and fine-tuning it

⭐ Main courses: Natural Language Processing, Large Language Models, Interactive Machine Learning: Visualization & Explainability, Probabilistic AI, Big Data for Engineers, AI4Good.
⭐ Master thesis "Enhancing Mid-Resource Language Performance in Large Language Models": end-to-end pipeline recipe for efficient bilingual LLM training and alignment (under supervision of prof. Vechev).
⭐ Extracurricular activities:
◆ Statistics representative at Seminar fur Statistik (SfS): organizing and leading events for students of Statistics MSc program
◆ Statistics MSc mentor: mentoring incoming first-year students of the program
◆ Member of VMP (student organization of D-MATH ETH department)

⭐ Master thesis: 'Modeling the investment portfolio of E-commerce companies':
◆ Twitter sentiment analysis of E-commerce stock tickers
◆ Stock prediction using Generative Adversarial Networks (GAN)
◆ Investment portfolio modeling (option hedge fund, stock portfolio prediction)

⭐ Grade: 94/100
◆ Graduated with honors
◆ Bachelor thesis: 'Modeling an equity investment fund using financial derivative management and hedging strategies'