Summary
Ali Hummos is a computational neuroscientist and postdoctoral researcher based in San Francisco with eight years of experience bridging biological principles and machine learning. He develops dynamical algorithms that expand computation into neural network weight matrices, drawing on top-down feedback control ideas inspired by the brain. His toolset spans Python, TensorFlow, PyTorch, deep reinforcement learning, and evolutionary methods, with applied work in audio-visual speech recognition and multi-object tracking. Founder of Synaptic Intelligence and former AI researcher at Deepen AI, he combines entrepreneurial drive with rigorous academic research at MIT. Trained as both an MD and a PhD in computational neuroscience, he uniquely blends clinical insight in psychiatry with algorithmic innovation, informing models grounded in biological plausibility.
8 years of coding experience
9 years of employment as a software developer
Doctor of Medicine (M.D.), Medicine, Doctor of Medicine (M.D.), Medicine at University of Jordan
University of Missouri