Driton Salihu is a Senior Researcher and PhD candidate in computer vision and machine learning with nine years of experience bridging academic research and industrial R&D in Munich. He specializes in 3D indoor reconstruction, multimodal scene understanding, and efficient latent representations, with publications at ICLR, ICASSP, WACV and ICRA. His work spans NeRF, Gaussian Splatting, diffusion models and RGB‑D point cloud processing, and he has applied these techniques to practical problems like AR illumination estimation and hardware‑aware CNN optimization. At Huawei he now focuses on reliable generative AI, building on prior projects at TUM, BMW and Nokia that combined deep learning, quantization/NAS and real‑time systems. He pairs strong hands‑on skills in C++, Python and Unity with teaching experience in DSP and software engineering labs, and a knack for turning complex mathematical ideas into efficient, deployable pipelines. An underappreciated strength is his consistent focus on hardware‑aware methods, enabling high‑performance models on constrained platforms.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Vision / Machine Learning, Doctor of Philosophy - PhD Computer Vision / Machine Learning at Technical University of Munich
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