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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Riadul Islam

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Open access Sep 2026

Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks

This work contributes a 2nd-order adaptive LIF neuron with two-stage synaptic filtering for richer temporal dynamics; a fully connected six-neuron spiking network with configurable weights demonstrating weight-based inter-neuron communication; and a direct verification methodology enabling per-cycle observation of all...

T. Pham, Riadul Islam · 0 citations
#artificial intelligence Preprint Sep 2026

DVA-Neurons: Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks

Spiking Neural Networks (SNNs) offer a promising path toward ultra-low-power artificial intelligence inference by emulating the event-driven computation of biological neurons. However, two challenges limit their practical deployment. First, fixed-parameter Leaky Integrate-and-Fire (LIF) neurons lack the adaptation mech...

T. Pham, Riadul Islam · 0 citations
#edge computing Preprint Aug 2026

LiteEvent-AE: Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices

A compact and configurable event-driven autoencoder that efficiently compresses neuromorphic data while preserving essential spatiotemporal structure for downstream inference and demonstrates the potential of compact event-driven models to advance environmentally conscious, low-power AI systems for high-speed perceptio...

Riadul Islam, Joey Mulé, Dhandeep Challagundla et al. · 0 citations
Open access Aug 2026

STGen: A Lightweight Process-Based Testbed for Scalable IoT Protocol Evaluation with Physically Validated Synthetic Sensor and Anomaly Generation

Results show that STGen provides a scalable and reproducible bridge between lightweight protocol emulation and practical deployment-oriented IoT protocol evaluation, and exposes deployment-relevant behavior that controlled emulation alone may hide.

H. Islam, M. M. Maharaz, M. Georgiades et al. · 0 citations

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