AI Researcher and PhD Candidate developing novel machine learning algorithms and scalable AI systems. My work spans brain-inspired AI, computer vision, robotics, and large-scale data analysis, with experience building high-performance machine learning software using Python, PyTorch, C++, CUDA, and HIP.
My research lies at the intersection of neuroscience, cognitive science, and machine learning. I study how principles of neural computation can inspire new learning algorithms and AI systems. For my PhD at KTH Royal Institute of Technology, I work with Pawel Herman and Anders Lansner on biologically inspired learning, credit assignment, associative memory, and the use of BCPNN as both a model of cortical learning and a machine-learning framework.bl
nbrav [at] kth [dot] se