Author

Shahmir Rizvi

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2026

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

Event-based vision has emerged as a promising paradigm for energy-aware artificial intelligence (AI), offering sparse, low-latency visual signals that reduce redundant data processing and support sustainable edge computing. However, the asynchronous and noise-prone nature of event streams creates challenges for convent...

Riadul Islam, Joey Mulé, Dhandeep Challagundla et al. · IEEE Canadian Journal of Ele... · 0 citations

Jul 2026

Risk Management Framework for LLM-Enabled Identity Tools: Mapping OWASP LLM Top 10 to NIST CSF 2.0

Large language models (LLMs) are increasingly embedded in identity and access management (IAM) tools that support workflows such as account recovery, access request triage, provisioning, policy interpretation, and privileged access handling. In these settings, security risk is often dominated not by the model in isolat...

Sanaa S. Mironov, Shahmir Rizvi, B. Shariati · 2026 IEEE European Symposium... · 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