Papers

10

Total Citations

117

H-Index

7

About

Adina Magda Florea is a prominent researcher whose work spans social robotics, human action recognition, and multi-robot systems. Her most significant contributions lie at the intersection of artificial intelligence and robotics, where she has advanced the capability of autonomous systems to perceive, interpret, and respond to human behavior in real-world environments. Florea's most cited work (37 citations) examines deep learning approaches — comparing recurrent networks with temporal convolutional networks — for skeleton-based action recognition, a foundational challenge in enabling robots to understand human activity. This research directly supports her broader agenda in social assistive robotics, particularly her development of the AMIRO Social Robotics Framework (27 citations), which was successfully deployed on the Pepper robot to deliver practical assistance in retail and care settings. Her contributions extend to user detection and re-identification, modular human-robot interaction frameworks, and graph convolutional models for real-time action recognition. Beyond social robotics, Florea has made meaningful strides in swarm robotics, designing low-cost miniature platforms and decentralized multi-robot coordination algorithms. Her research portfolio reflects a rare breadth — from cutting-edge neural architectures to deployable robotic systems — making her a valuable reference for students working in intelligent autonomous systems, human-computer interaction, and assistive technology.

Research Focus

Key Achievements

7
H-Index
10
Papers
117
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Comparison between Recurrent Networks and Temporal Convolutional Networks Approaches for Skeleton-Based Action Recognition
37 citations · 2021
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Universitatea Națională de Știință și Tehnologie Politehnica București, University of Bucharest

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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