Navid Rekabsaz
Lead Applied Scientist at Thomson Reuters
Switzerland
Summary
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Senior🎓
Top SchoolNavid Rekabsaz is a Lead Applied Scientist based in Switzerland with 11 years of experience building and leading NLP and IR research-to-production initiatives. He combines an academic pedigree (PhD from TU Wien) and a track record as an assistant professor and postdoc with hands-on industry work delivering RAG, QA, summarization, and domain-specific NLP systems for climate and humanitarian partners. At Thomson Reuters he progressed from Senior to Lead Applied Scientist, and his advisory role at Data Friendly Space highlights experience running small ML teams and deploying impactful, mission-driven solutions. His research emphasizes trustworthy NLP, bias and fairness in IR, and parameter-efficient transfer learning—skills he teaches and operationalizes. Notably, he bridges deep research rigor with practical deployment, translating complex neural-IR advances into usable tools for real-world decision making.
11 years of coding experience
19 years of employment as a software developer
Vienna University of TechnologyBachelor of Science, Computer Science – Software, Bachelor of Science, Computer Science – Software at Iran University of Science and Technology
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (27)
python8
deep-learning8
gpu8
machine-learning8
neural-network6
tensorflow6
numpy5
mms5
react3
gpu-acceleration3
evaluation3
acceleration3
tensor3
retrieval2
autograd2
Programming languages (4)
Github contributions (5)
neds/semanticsim
Jan 2015 - Dec 2017
Contributions:645 pushes in 2 years 11 months
navid-rekabsaz/GenderBias_IR
May 2020 - Jun 2021
Contributions:10 commits, 9 pushes, 1 branch in 1 year 1 month
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