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Parsa Research Laboratory

Welcome to PRL!
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Parsa Research Laboratory (PRL) was born on 08/25/2021 at George Mason University in the Electrical and Computer Engineering department of the Volgenau School of Engineering, College of Engineering and Computing.

At PRL, we believe in taking inspiration from brain to advance cognitive computing and enable novel autonomous intelligent systems for edge computing and large-scale distributed learning. We specifically focus on omnidirectional microelectronics co-design to produce safe, robust, and resilient neuromorphic systems. We have broad interests in the areas of cognitive computing (cognitive vision and cognitive memory), neuromorphic computing, hyperdimensional computing, evolutionary and Bayesian learning, physics-informed intelligence, neural architecture search and multi-objective optimization across the full stack of materials, devices, circuits, systems, algorithms, and applications. In addition, we are developing novel hierarchical learning/training approaches based on evolutionary, Bayesian, and synaptic learning rules. We are interested in wide range of applications such as communication and signal processing, control and robotics, smart healthcare, smart grid, and cyber-physical systems.

News & Updates

2023
  • Dr. Parsa is an invited speaker at the IEEE Annual Conference on Information Sciences and Systems (CISS) Special Session on Low Power Autonomous and Smart Systems.
  • Shay Snyder will present a poster on “Evolved Spiking Neural Networks for SWaP-Constrained Autonomous Agents” at Neuro-Inspired Computational Elements Conference.
  • Shay Snyder will present a poster on “Zespol: A Lightweight Environment for Training Swarming Agents” at Neuro-Inspired Computational Elements Conference.

  • 2022
  • PRL received a grant from U.S. Army’s Automotive Research Center for work in Multi-Phase Vector Symbolic Architectures for Distributed and Collective Intelligence in Multi-Agent Autonomous Systems ($126,000 per year).
  • PRL received a gift from Leidos for collaboration on neuromorphic computing, algorithms and applications ($10,000).
  • Shay Snyder’s work on Lava-BayesianOptimization was merged to Intel’s Lava Optimization library and was officially the first external contribution to this library.
  • Dr. Parsa was an invited speaker at the Intel Neuromorphic Research Community (INRC) Forum.
  • Shay Snyder’s work on Lava-BayesianOptimization was merged to Intel’s Lava Optimization library and was officially the first external contribution to this library.
  • Dr. Parsa was an invited speaker at the Laboratory for Applied Mathematics, Numerical Software, and Statistics at Argonne National Laboratory.
  • Dr. Parsa was an invited speaker at The Center for Neural Informatics, Neural Structures, and Neural Plasticity (CN3).