Alexander G. Ororbia II

Alexander G. Ororbia II is an Assistant Professor in the Department of Computer Science at Rochester Institute of Technology (RIT), where he directs the Neural Adaptive Computing (NAC) Laboratory. He is also an affiliate professor in the RIT Department of Psychology, an affiliate faculty member of RIT's Center for Applied Neuroscience, and affiliate faculty in RIT's Cognitive Science program. Ororbia received his Ph.D. in Information Science & Technology from Penn State University and a B.S.E. in Computer Science & Engineering from Bucknell University.

His research focuses on developing computational models of neural information processing and synaptic plasticity, with significant contributions to predictive coding, active inference, spiking neural networks, neural-based cognitive modeling, and neurorobotic control. As Director of the NAC Laboratory, he leads research on biomimetic intelligence and brain-inspired computing, specifically developing neurocognitively plausible approaches to adaptation and memory formation in artificial neural systems.

His publication trends show a strong focus on brain-inspired computing, with particular emphasis on predictive coding frameworks, active inference models, and spiking neural networks. Recent work has advanced the fields of lifelong machine learning, biomimetic intelligence, and backpropagation alternatives, with applications in robotics, computer vision, and cognitive modeling. His research bridges machine learning, computational neuroscience, and cognitive science to create more robust and adaptive artificial intelligence systems.

• IGERT Fellow
• NACME Sloan Scholar
• Jordan-Rednor Scholarship
• Bunton-Waller Scholarship

Ororbia advises numerous Ph.D. and M.Sc. students working on projects related to spiking neural networks, predictive coding, active inference, and lifelong machine learning. His lab has secured research funding that supports multiple graduate students and postdoctoral researchers. The NAC Laboratory collaborates with institutions including Penn State University and has produced research published in top-tier venues including Nature Communications, Science Advances, NeurIPS, and ICRA.

The NAC Laboratory, under Ororbia's direction, focuses on neurocognitively-inspired lifelong machine learning, developing novel learning algorithms and memory architectures for artificial neural systems. The lab explores both non-spiking and spiking neural networks, with applications in robotics, computer vision, and cognitive modeling. Current research directions include predictive processing implementations of cognitive architectures, mortal computation frameworks, and biologically plausible alternatives to backpropagation.