Maryam Vahabi

ABB (Sweden), Mälardalen University

Papers

2

Total Citations

118

H-Index

2

About

Maryam Vahabi is a researcher whose work bridges artificial intelligence and the Internet of Things (IoT), with a particular focus on human behavior analysis and industrial automation. Her most impactful contribution, a 2020 study on hybrid deep learning models for Human Activity Recognition (HAR), has garnered 113 citations, reflecting the field’s explosive growth and her role in advancing effective ML-based tools for analyzing human behavior across diverse applications. In parallel, Vahabi has explored the Industrial Internet of Things (IIoT), developing an analytical model for deploying mobile sinks—such as data-collecting robots—to enhance manufacturing efficiency in smart factories. This work addresses the practical challenge of integrating mobile robots into industrial supply chains, showcasing her ability to tackle real-world engineering problems. By combining deep learning with IoT architectures, Vahabi’s research not only pushes the boundaries of automated activity recognition but also provides scalable solutions for next-generation industrial systems. Her work stands as a valuable resource for students and researchers interested in the intersection of AI, pervasive computing, and cyber-physical systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
118
Total Citations
59
Avg Citations/Paper
🏆 Most Cited Paper
A Comparative Analysis of Hybrid Deep Learning Models for Human Activity Recognition
113 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: ABB (Sweden), Mälardalen University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago