Summary
Ata Karagoz is a computational neuroscientist and machine learning researcher with 9 years of experience developing and deploying RL, RNN, and advanced statistical models to probe human decision-making, memory, and spatial navigation. Currently a postdoctoral fellow at the University of Chicago after a PhD at Washington University in St. Louis, he has accelerated model development and neuroimaging analyses—achieving up to 10x faster model fitting and 40x speedups on HPC pipelines—while publishing first-author papers and securing significant grant funding. His work blends principled cognitive modeling with practical engineering (Python, PyTorch, JAX, MATLAB), translating complex neural and behavioral data into actionable insights about human planning and inference. Notably, he has combined transformer embeddings and brain decoding to study social learning and devised novel behavioral measures to quantify internal planning models, demonstrating a knack for creating new tools and metrics that reveal subtle aspects of cognition.
9 years of coding experience
9 years of employment as a software developer
Bachelor of Science - BS, Neuroscience, Bachelor of Science - BS, Neuroscience at The University of Texas at Austin
Doctor of Philosophy - PhD, Psychological and Brain Sciences, Doctor of Philosophy - PhD, Psychological and Brain Sciences at Washington University in St. Louis