Estefanos Kebebew
Interested at the intersection of algorithms and biology
My Focus
I am a software developer by training with a growing foundation in biology. I am deeply interested in how modern algorithms and computational methods are transforming biological research. Iām continuously learning and driven by the challenge of solving complex problems with robust, scalable, and well-designed code.
I am open to opportunities in both biotech research & development and software/ML engineering, where I can apply my hybrid skill set to build impactful, data-driven solutions.
Research & Projects
š Master's Thesis: Predicting AMR with Deep Learning
- Problem: Traditional lab methods for testing Antimicrobial Resistance (AMR) are slow, delaying crucial treatments.
- Solution: Developed and compared machine learning models (CNNs, Random Forest, XGBoost) to predict AMR in E. coli directly from genomic SNP data.
- Impact: This computational approach aims to reduce prediction time providing rapid, actionable insights for clinical and research settings.
āļø Thesis Pipeline
Posters
Technical Skills
š§¬ Bioinformatics & Data Science
š¤ ML / Deep Learning
š„ TensorFlow / PyTorch
š Pandas / NumPy
š Matplotlib / Seaborn
š§¬ Roary / Snippy
š§¬ SRA Toolkit
š§¬ LDpred / PRSice
šļø UK Biobank Data
š» Software Engineering & DevOps
š Python
ā Java / Spring
āļø React
šļø SQL / PostgreSQL
āļø AWS
š Docker
š Git / GitHub
š§ Linux / Shell Scripting