Summary
Gereziher Adhane is a Postdoctoral Researcher in Barcelona with a PhD in AI and a decade of experience building and optimizing deep learning systems for computer vision and multimodal models. He has hands-on expertise across convolutional, recurrent, variational, generative, transformer and Bayesian networks, plus practical work on LLM fine-tuning, prompt engineering, Graph-RAG and GANs, primarily in PyTorch and Python. His recent work at the Computer Vision Center focuses on general multimodal foundation models and HPC, following industry-facing AI engineering at Iquadrat and explainability research during his PhD. Gereziher combines strong academic rigor with production-aware engineering—skilled in scaling models, distributed AI, 3D vision and AI optimization techniques that bridge research and deployment. Fluent in additional languages and tools (TensorFlow, C++, Java, MATLAB), he brings a rare mix of theoretical depth and systems-level focus that accelerates model adoption in real-world settings.
10 years of coding experience
3 years of employment as a software developer
UOC (Universitat Oberta de Catalunya)
English, Tigrinya, Amharic