4 citations · 6 across the 6 of their papers we have counts for
6 papers
MCP Bridge: A Lightweight, LLM-Agnostic RESTful Proxy for Model Context Protocol Servers
Arash Ahmadi, Sarah Sharif, Yaser M. Banad
Large Language Models (LLMs) are increasingly augmented with external tools through standardized interfaces like the Model Context Protocol (MCP). However, current MCP implementati…
Accelerated Discovery of Vanadium Oxide Compositions: A WGAN-VAE Framework for Materials Design
Danial Ebrahimzadeh, Sarah S. Sharif, Yaser M. Banad
The discovery of novel materials with tailored electronic properties is crucial for modern device technologies, but time-consuming empirical methods hamper progress. We present an…
Dual Micro-Ring Resonators with Angular GST Modulation: Enabling Ultra-Fast Nonlinear Activation for Neuromorphic Photonics
Hossein Karimkhani, Yaser M. Banad, Sarah Sharif
Photonic technologies are emerging as powerful enablers for neuromorphic computing by delivering ultrafast and energy efficient neural functionalities. In this work, we propose and…
Investigating the Effect of Electrical and Thermal Transport Properties on Oxide-Based Memristors Performance and Reliability
Armin Gooran-Shoorakchaly, Sarah Sharif, Yaser Banad
Achieving reliable resistive switching in oxide-based memristive devices requires precise control over conductive filament (CF) formation and behavior, yet the fundamental relation…
On-Chip Learning with Memristor-Based Neural Networks: Assessing Accuracy and Efficiency Under Device Variations, Conductance Errors, and Input Noise
M. Reza Eslami, Dhiman Biswas, Soheib Takhtardeshir +2
This paper presents a memristor-based compute-in-memory hardware accelerator for on-chip training and inference, focusing on its accuracy and efficiency against device variations,…
A Comparative Study of Sampling Methods with Cross-Validation in the FedHome Framework
Arash Ahmadi, Sarah S. Sharif, Yaser M. Banad
This paper presents a comparative study of sampling methods within the FedHome framework, designed for personalized in-home health monitoring. FedHome leverages federated learning…