Summary
Haris Organtzidis is a research-focused computational neuroscientist and engineer with eight years of experience applying Bayesian inference and reinforcement learning theory to human-centric problems in perception, memory, and motor control. He transitioned from modeling energetics and control in prosthetics during his MSc to a PhD investigating subtle bias measurements in anxiety and depression, combining theoretical models with behavioral experiments while explicitly quantifying multiple sources of uncertainty. Based in Athens, he has blended academic research with engineering roles across projects like Turing.jl, Julia Computing, and EEGVIBE, bringing production-aware probabilistic programming experience to neurodiagnostics applications. Currently collaborating at Neuroblox and contributing to translational research at the Laboratory for Computational Neurodiagnostics, he mentors via Neuromatch to help train the next generation in computational methods. Haris’s work is notable for marrying principled Bayesian methods with practical experimental design—an approach that surfaces latent cognitive biases before clinical symptoms emerge.
8 years of coding experience
1 year of employment as a software developer
Diploma of Mechanical Engineering, Mechanical Engineering, Diploma of Mechanical Engineering, Mechanical Engineering at Aristotle University of Thessaloniki (AUTH)
Doctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at University of Bristol