activity
20242026
most citedLeveraging Blockchain and ANFIS for Optimal Supply Chain Management

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2026

TA-RNN-Medical-Hybrid: A Time-Aware and Interpretable Framework for Mortality Risk Prediction

Zahra Jafari, Azadeh Zamanifar, Amirfarhad Farhadi

Accurate and interpretable mortality risk prediction in intensive care units (ICUs) remains a critical challenge due to the irregular temporal structure of electronic health record…

cs.LG2026

Deep Reinforcement Learning for Optimizing Energy Consumption in Smart Grid Systems

Abeer Alsheikhi, Amirfarhad Farhadi, Azadeh Zamanifar

The energy management problem in the context of smart grids is inherently complex due to the interdependencies among diverse system components. Although Reinforcement Learning (RL)…

cs.CV2026

SCA-Net: Spatial-Contextual Aggregation Network for Enhanced Small Building and Road Change Detection

Emad Gholibeigi, Abbas Koochari, Azadeh ZamaniFar

Automated change detection in remote sensing imagery is critical for urban management, environmental monitoring, and disaster assessment. While deep learning models have advanced t…

cs.CR2026

TinyGuard:A lightweight Byzantine Defense for Resource-Constrained Federated Learning via Statistical Update Fingerprints

Ali Mahdavi, Santa Aghapour, Azadeh Zamanifar +1

Existing Byzantine robust aggregation mechanisms typically rely on fulldimensional gradi ent comparisons or pairwise distance computations, resulting in computational overhead that…

cs.LG2025

SILS: Strategic Influence on Liquidity Stability and Whale Detection in Concentrated-Liquidity DEXs

Ali RajabiNekoo, Laleh Rasoul, Amirfarhad Farhadi +1

Traditional methods for identifying impactful liquidity providers (LPs) in Concentrated Liquidity Market Makers (CLMMs) rely on broad measures, such as nominal capital size or surf…

cs.CV2025

Source-Free Domain Adaptation via Multi-view Contrastive Learning

Amirfarhad Farhadi, Naser Mozayani, Azadeh Zamanifar

Domain adaptation has become a widely adopted approach in machine learning due to the high costs associated with labeling data. It is typically applied when access to a labeled sou…