7 papers
Real-Time Personalized Content Adaptation through Matrix Factorization and Context-Aware Federated Learning
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Our study presents a multifaceted approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. We introduce person…
Optimus-Q: Utilizing Federated Learning in Adaptive Robots for Intelligent Nuclear Power Plant Operations through Quantum Cryptography
Sai Puppala, Ismail Hossain, Jahangir Alam +1
The integration of advanced robotics in nuclear power plants (NPPs) presents a transformative opportunity to enhance safety, efficiency, and environmental monitoring in high-stakes…
LLM-Guided Dynamic-UMAP for Personalized Federated Graph Learning
Sai Puppala, Ismail Hossain, Md Jahangir Alam +2
We propose a method that uses large language models to assist graph machine learning under personalization and privacy constraints. The approach combines data augmentation for spar…
Variational Gaussian Mixture Manifold Models for Client-Specific Federated Personalization
Sai Puppala, Ismail Hossain, Md Jahangir Alam +1
Personalized federated learning (PFL) often fails under label skew and non-stationarity because a single global parameterization ignores client-specific geometry. We introduce VGM$…
AI-in-the-Loop: Privacy Preserving Real-Time Scam Detection and Conversational Scambaiting by Leveraging LLMs and Federated Learning
Ismail Hossain, Sai Puppala, Md Jahangir Alam +1
Scams exploiting real-time social engineering -- such as phishing, impersonation, and phone fraud -- remain a persistent and evolving threat across digital platforms. Existing defe…
EVOLVE-X: Embedding Fusion and Language Prompting for User Evolution Forecasting on Social Media
Ismail Hossain, Sai Puppala, Md Jahangir Alam +1
Social media platforms serve as a significant medium for sharing personal emotions, daily activities, and various life events, ensuring individuals stay informed about the latest d…