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Danila Lissovoy

@daNickConnected with DSML. This person's Telegram account has been confirmed through DSML Kazakhstan.

ML/AI Engineer interested in applied AI roles

AI/ML Engineer | Data Scientist — CS graduate from Nazarbayev University with research published at IEEE ICIP, specializing in RAG systems, AI Agents and NLP.

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Career

Experience: 1 years

Experience

Research Assistant

Nazarbayev University

A university in Astana, Kazakhstan, with an Institute of Smart Systems and Artificial Intelligence.

Feb 2025 — Present

Developed and evaluated ML models for hyperspectral imaging and object detection, processed large image datasets, and supported an ML-powered food-analysis app.

• Developed and benchmarked machine learning models (XGBoost, SVM, CNN) for hyperspectral image regression, supporting research on food quality and sustainability through remote sensing techniques. • Collected and processed a dataset of 1,760 hyperspectral images (300GB), reduced it to 80GB without data loss through optimized preprocessing and feature selection. • Conducted testing and benchmarking of YOLO-based object detection models for the custom image dataset containing 34,145 images, validating dataset quality and model performance.

Data Science Intern

Financial Monitoring Agency of the Republic of Kazakhstan

A government agency of Kazakhstan responsible for financial monitoring.

Jun 2023 — Aug 2023

Collected and cleaned financial and public-sector data, automated portal data extraction, and supported analysis for monitoring projects.

• Collected and cleaned financial and public sector data using Python (BeautifulSoup, Pandas) and Excel for internal analytical reports. • Built scripts to automate data extraction from government web portals and transform outputs into structured Excel/CSV formats. • Assisted in exploratory analysis and documentation of financial transaction data to support ongoing monitoring projects.

Education

Bachelor of Science, Computer Science

Nazarbayev University

2022 — 2026

Selected projects

Local Multilingual Document Q&A System with Source Citations

Built a multilingual hybrid RAG application for legal documents with source citations, evaluation across Russian, Kazakh, and English, language-aware prompting, asynchronous PDF ingestion, and on-premise LLM inference. Reported hit@5 of 0.95, MRR of 0.86, citation accuracy above 85%, and a reduction of over 60% in answer-language mismatch.

Interactive Biomedical Question Answering with T5

Built and evaluated T5-small and T5-base biomedical question-answering models on BioASQ, then deployed the best model as an interactive web application. Fine-tuning improved BLEU by up to 16%, semantic similarity by 6%, and exact match accuracy by 33%.

Face Detection and Super-Resolution for CCTV Recognition

Built a face detection and super-resolution pipeline for low-resolution CCTV imagery, modifying SwinIR-light with reconstruction, perceptual, and identity losses. Reported gains over bicubic upsampling in PSNR and SSIM, reduced identity loss, and improved verification reliability compared with the stated baseline.

Achievements

2nd Place, Higgsfield AI Case Championship

Higgsfield AI · 2025

Dean’s List

Nazarbayev University · 2023

Dean’s List

Nazarbayev University · 2024

Skills

PythonSQLHTMLCSSC/C++JavaScriptGitFastAPIFlaskPandasSeabornMatplotlibNumPyPyTorchTensorFlowScikit-LearnPostgreSQLDockerOllamaLangChain