Seyed Mohammad Azimi-Abarghouyi
Scholar

Seyed Mohammad Azimi-Abarghouyi

Google Scholar ID: xKe1vyMAAAAJ
KTH Royal Institute of Technology
Wireless CommunicationsEdge AIFederated LearningMachine Learning
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Citations & Impact
All-time
Citations
229
 
H-index
8
 
i10-index
7
 
Publications
20
 
Co-authors
0
 
Contact
Emailseyaa@kth.seTwitterOpen ↗LinkedInOpen ↗
Publications
11 items
Progressive-Resolution Secure Aggregation for Federated Learning
2026
Cited
0
FedHV: Low-Overhead Hypervolume Weighting for Federated Multi-Objective Optimization
2026
Cited
0
Occupancy-Domain Over-the-Air Computation
2026
Cited
0
FullPASS: Geometry Optimization for Full-Duplex Pinching-Antenna Systems
2026
Cited
0
AirPASS: Over-the-Air Federated Learning via Pinching Antenna Systems
2026
Cited
0
Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design
2026
Cited
0
Out-of-Air Computation: Enabling Structured Extraction from Wireless Superposition
2026
Cited
0
Hierarchical Federated Learning with SignSGD: A Highly Communication-Efficient Approach
2026
Cited
0
Resume
Academic Achievements
  • No specific information provided.
Research Experience
  • Currently a Senior Researcher at KTH Royal Institute of Technology. Before this role, he was a Postdoctoral Fellow at KTH from 2021 to 2024.
Education
  • Earned MSc and PhD degrees from Sharif University of Technology, Tehran, Iran, in 2014 and 2020, respectively.
Background
  • Research interests include Theories of Communication, Coding, and Optimization, Distributed Computation and Optimization, Machine Learning and Federated Learning, Edge Computing and AI, Wireless Communications and Networking.
Miscellany
  • Contact:
  • - Email: seyaa@kth.se
  • - Google Scholar, LinkedIn, Twitter