About
About Me
I'm an Applied Scientist working at the intersection of machine learning, natural language processing, and knowledge representation. I build systems that extract meaning from data — and make those systems work reliably at scale.
My research focuses on federated query processing, knowledge graphs, and privacy-aware data systems. I care deeply about the gap between research and production: building systems that don't just benchmark well, but actually hold up in the real world.
Experience
Applied Scientist II
Amazon
Leading research and development of multilingual NLP systems for large-scale product understanding. Shipped models serving hundreds of millions of customers across 15 languages.
Applied Scientist
Amazon
Developed entity resolution and knowledge graph completion systems for Amazon's product catalog. Reduced duplicate entity rate by 34% across major product categories.
PhD Researcher
Leibniz University of Hannover
Doctoral research on scalable federated query processing and privacy-aware knowledge graph systems. Affiliated with the SDM-TIB group. Built Ontario, MULDER, and BOUNCER — open-source engines for federated SPARQL over semantic data lakes.
MSc Researcher
University of Trento
Graduate research in service design and engineering. Built LifeCoachService, a health and lifestyle monitoring web service, as part of coursework in service-oriented architectures.
Education
2017 — 2021
PhD, Computer Science
Leibniz University of Hannover
Federated query processing and knowledge graph systems (SDM-TIB group)
2015 — 2017
MSc, Computer Science
University of Trento
Service design, engineering, and distributed systems
2010 — 2014
BSc, Computer Science
University of Gondar
Graduated with distinction
Let's connect.
Open to research collaborations, applied science roles, and interesting problems.