Damir Sarsengaliyev

Data scientist working on statistics, machine learning, and LLMs.

About

I have a BSc in Computer Science from Nazarbayev University and studied Statistics and Data Science at MBZUAI. I've worked as a software engineer, data engineer, and research assistant on audio and multimodal ML. I like problems where careful statistics meets messy real-world data.

Projects

Agentic Legal GraphRAG

A tool-calling agent over 1,000+ Omani legal documents that answers multi-hop questions, like tracing amendment and repeal chains across laws. Combines dense + BM25 retrieval with rank fusion, cross-encoder reranking, and Neo4j graph traversal across Arabic and English.

Python · Neo4j · Groq · RAG

Prediction Market Calibration

How public attention affects calibration in prediction markets, using 679K Kalshi contracts and 72M trades. Clustered markets into five types, validated with Kruskal-Wallis and Dunn tests, and tested Granger causality against Google Trends.

DuckDB · scikit-learn · UMAP · FAISS

Activation Steering in Small LLMs

Found skill-specific directions in the residual stream of Qwen3-4B, with peak separability in middle layers, and compared several steering-vector strategies on math benchmarks.

PyTorch · Interpretability · MATH-500

Multimodal Emotion Recognition

Video, audio, and text model reaching 90%+ accuracy on IEMOCAP, deployed as a real-time web app.

PyTorch · ConvNeXt · RoBERTa

Skills

Python, SQL, Java, C++ · Pandas, NumPy, SciPy, scikit-learn, PyTorch · XGBoost, LightGBM, CatBoost · DuckDB · Statistical testing and experimental design