Summary
Girmaw Tadesse is a Principal Research Scientist and manager at Microsoft AI for Good Lab and a current member of the UN's Independent International Scientific Panel on AI, bringing nine years of cross-sector experience in trustworthy and applied AI. He previously led research on Trustworthy AI at IBM and conducted postdoctoral work at Oxford, focusing on machine learning for healthcare decision support in low-resource settings, especially infectious and cardiovascular disease diagnostics. His technical repertoire spans cross-domain transfer learning between physiological time-series and computer vision, multimodal fusion (video, inertial, audio), and pioneering first-person vision from wearable cameras for activity recognition. Girmaw combines strong academic collaborations with Harvard, Stanford and Oxford with practical impact, designing resource-aware models that incorporate expert feedback and decision confidence. Based in Kenya, he blends deep research pedigree (PhD-era work across Queen Mary, UPC and Trento) with operational leadership in global AI policy and applied health technologies. An often-overlooked strength is his track record of adapting advanced vision and signal techniques to real-world, resource-constrained clinical workflows.
9 years of coding experience
7 years of employment as a software developer
MSc, Telecommunications Engineering, MSc, Telecommunications Engineering at Università di Trento
Bachelor of Science (BSc), Electrical Engineering, Bachelor of Science (BSc), Electrical Engineering at Arba Minch University
University of Oxford
Doctor of Philosophy (PhD), Erasmus Mundus Joint/Double Doctorate Programme in Interactive and Cognitive Environments, Doctor of Philosophy (PhD), Erasmus Mundus Joint/Double Doctorate Programme in Interactive and Cognitive Environments at Queen Mary University of London
UPC Universitat Politècnica de Catalunya
English, spanish (a2), italian (a1), Amharic