Professor of Computational Cognition
& Human–Machine Intelligence
Exploring how minds—biological and artificial—encode, retrieve, and reason about knowledge at scale. My lab bridges cognitive science, deep learning, and interactive systems to build machines that understand context the way people do.
Dr. Evelyn Hartley leads the Computational Cognition Lab (CCL) at Northgate University. Her work sits at the intersection of cognitive architecture, large-scale neural networks, and explainable AI — building systems that don't just perform tasks, but reason transparently about them.
Before joining Northgate, she was a research scientist at the Allen Institute for Artificial Intelligence and completed her doctoral work at MIT's Brain & Cognitive Sciences department under Prof. Joshua Tenenbaum.
A neural-symbolic architecture that generates human-readable explanations for deep network decisions by grounding activations in cognitive schemas. Funded by DARPA XAI Programme.
Extending BPL frameworks to operate across thousand-concept domains with sparse human supervision.
Studying how AI advisory systems shape human judgment in clinical and legal reasoning contexts.
Training language models to resolve referential ambiguity through simulated physical interaction with environments.
A rigorous introduction to ML theory: statistical learning, probabilistic models, optimization, and neural networks. Enrollment: 120 students.
Covers probabilistic models of cognition, Bayesian inference, program induction, and the interface between AI and psychology.
Deep dive into interpretability methods: SHAP, LIME, concept-based explanations, mechanistic interpretability, and human evaluation.
CCL alumni hold faculty positions at CMU, UCSD, and ETH Zürich, and research roles at Google DeepMind, Meta AI, and OpenAI.
Join the Lab →