معرفی
Oliver Layton is an Associate Professor and Associate Chair of the Computer Science Department at Colby College, Maine. His research bridges computational neuroscience and machine learning, focusing on neural modeling of visual perception and self-motion estimation. He teaches courses in Mathematical Data Analysis and Visualization (CS252), Neural Networks (CS343), and Deep Learning (CS444).
- Postdoctoral scholar, Rensselaer Polytechnic Institute
- Ph.D., Cognitive and Neural Systems, Boston University
- B.A., Mathematics and Computational Neuroscience, Skidmore College
His expertise spans computational neuroscience, neural modeling, and visual perception, with emphasis on optic flow processing and its applications. Research explores how biological systems (like primate MSTd) estimate heading and self-motion, using biologically inspired neural networks and dynamic sensory encoding models.
Recent publications focus on deep learning approaches to optic flow analysis, heading perception stability, and curvilinear motion modeling. Key trends include applying convolutional neural networks to simulate MSTd tuning, investigating sparseness and ReLU activation impacts, and comparing human and AI performance in self-motion estimation tasks.
