Samaneh Mohammadi
Scholar

Samaneh Mohammadi

Google Scholar ID: hVsI_-4AAAAJ
PhD Researcher, RISE Research Institutes of Sweden
Federated LearningDistributed AIAI Privacy
Citations & Impact
All-time
Citations
102
 
H-index
4
 
i10-index
4
 
Publications
10
 
Co-authors
9
list available
Resume (English only)
Academic Achievements
  • - Publications:
  • - EncCluster: Scalable Functional Encryption in Federated Learning through Weight Clustering and Probabilistic Filters, Pervasive and Mobile Computing Journal, 2025.
  • - Bringing Functional Encryption in Federated Foundational Models, NeurIPS 2024 Workshop on Federated Foundation Models.
  • - Balancing Privacy and Performance in Federated Learning: A Systematic Literature Review on Methods and Metrics, Journal of Parallel and Distributed Computing, 2024.
  • - Secure and Efficient Federated Learning by Combining Homomorphic Encryption and Gradient Pruning in Speech Emotion Recognition, ISPEC 2023.
  • - Balancing Privacy and Accuracy Federated Learning for Speech Emotion Recognition, FedCSIS 2023 (Best Paper Award).
  • - Hyperparameters optimization for federated learning system: Speech emotion recognition case study, FMEC 2023.
  • - Optimized paillier homomorphic encryption in federated learning for speech emotion recognition, IEEE COMPSAC 2023.
Research Experience
  • - Researcher at RISE Research Institute of Sweden
  • - Experience at the University of Tehran
  • - Work experience at Openinside Co.
  • - Actively involved in two major European research projects: DADAP Project (developing an AI model for mental health disorders using federated learning) and DAIS Project (applying privacy-preserving techniques in federated learning for industrial use-cases)
Education
  • - PhD: Mälardalen University
  • - MSc: Tehran University
Background
  • - Industrial PhD candidate with over five years of experience in AI and privacy-preserving machine learning
  • - Research interests include distributed machine learning, federated learning, AI privacy, and edge AI
  • - Focuses on scalable, secure, and efficient ML models for real-world distributed systems
Miscellany
  • - Contact Information:
  • - Email: samaneh.mohammadi@ri.se
  • - LinkedIn: samaneh-mohammadi
  • - Google Scholar: Profile