activity
20182026
most citedWireless Network Slicing: Generalized Kelly Mechanism Based Resource Allocation

77 citations · 109 across the 29 of their papers we have counts for

collaborators

50 papers

cs.NI2026

Energy-Latency Trade-offs in O-RAN with Distributed Baseband Processing and AI Inference

Urooj Tariq, Rishu Raj, Shashi Raj Pandey +3

The Open Radio Access Network (O-RAN) architecture introduces flexible functional splits and open interfaces that enable distributed and centralized deployment of baseband processi…

quant-ph2026

Quantum Compression for Distributed Entanglement

Jan Østergaard, Shashi Raj Pandey, Christophe Biscio +2

We study compression strategies for multipartite entanglement distribution under uncertainty in the partitioning of the quantum state. When the partition is not known at the time o…

cs.LG2026

Multi-Agent Conformal Prediction with Personalized Statistical Validity

Martin V. Vejling, Christophe A. N. Biscio, Adrien Mazoyer +2

Uncertainty quantification is essential in high-stakes machine learning tasks. However, one of the principled solutions, conformal prediction, faces challenges under limited local…

cs.LG2026

Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts

Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3

In this work, we present OCLADS, a novel communication framework with continual learning (CL) for Internet of Things (IoT) anomaly detection (AD) when operating in non-stationary e…

eess.SP2026

Goal-Oriented Access Optimization for ISAC-Enabled Digital Twins

Fabio Saggese, Federico Chiariotti, Shashi Raj Pandey +3

Digital twins (DTs) of physical systems enable real-time remote tracking, control, and learning, but require to be updated with environmental sensory data to maintain alignment wit…

cs.IT2026

Type-Based Unsourced Federated Learning With Client Self-Selection

Kaan Okumus, Khac-Hoang Ngo, Unnikrishnan Kunnath Ganesan +3

We address the client-selection problem in federated learning over wireless networks under data heterogeneity. Existing client-selection methods often rely on server-side knowledge…