Michael Furlong

Michael Furlong is an Adjunct Assistant Professor at the University of Waterloo. His research bridges neuroscience and computer science, focusing on neuromorphic computing, vector symbolic architectures, and autonomous robotic systems. He has contributed to frameworks like Neurobench for evaluating neuromorphic algorithms and developed models for cognitive processes such as visual attention and action specification.

• Email: michael.furlong@uwaterloo.ca

Research Interests: His work explores biologically plausible computation, spiking neural networks, and Bayesian optimization. Publications highlight autonomous exploration, terrain classification, and information-gathering strategies for planetary missions. Collaborative projects emphasize fair benchmarking and robust adaptive recovery in robotic systems.

Recent Trends: Recent articles focus on hyperdimensional computing, probabilistic neuromorphic programming, and multi-modal active perception. These studies integrate category theory, dynamic modeling, and semantic processing to advance neuromorphic hardware and cognitive architectures.

Key Collaborations: Participated in planetary exploration initiatives, including lunar rover simulation and icy moon landing site selection, combining Wald's sequential probability ratio test for fault tolerance and neural predictive control for robotic chassis reconfiguration.