Overview
Data Scientist · Machine Learning · Systems
With a background in mathematics, computer science, and computational neuroscience, I enjoy working on applied machine learning and data-driven systems. I focus on building reliable models, clear analysis, and practical tools that support real decisions.
Selected Projects
tNet Analysis
(temporal graphs)
2024
Modular toolkit for constructing, simulating, and analyzing temporal networks, with integration and segregation metrics.
Temporal graphs, Null models, Random walks, Clustering, Modularity
Coffee Market Analytics
(LLM-assisted pipeline)
2025
Reproducible time-series analytics pipeline for commodity price data, from ingestion and feature engineering to modeling and evaluation.
Time-series, Snakemake, SQLite, Baseline model, Ollama
Amharic Normalization & Canonical Representation
(Canonical Orthographic Framework)
2025
Deterministic orthographic normalization framework for Amharic, featuring a reversible canonical representation (CAR), ambiguity-aware Latin decoding, and bidirectional punctuation standardization.
Canonical encoding, Transliteration, Orthographic normalization, FastAPI, Linguistic infrastructure, NLP preprocessing
Focus
- Data science workflows: from exploration to decision-ready insights
- Machine learning: evaluation, robustness, and responsible deployment
- Systems: APIs, dashboards, and tools that make models usable