Research Interests
- Cybersecurity in Networked and Distributed Systems
- Fog/Cloud Computing Architectures and Resource Scheduling
- Privacy-Preserving Machine Learning and Federated Learning
- Internet of Things (IoT) and Cyber-Physical Systems
- High-Performance Computing (HPC) Task Scheduling and Optimization
Education
M.Sc. in Computer Networks
GPA: 4.00/4.00
B.Sc. in Computer Engineering
GPA: 3.95/4.00
Publications
Priority-Aware SDN Orchestration for Surgical IoMT: A Joint Optimization of Hit Ratio and Latency with Dynamic Resource Reallocation.
IEEE Access, 2025.
Spotting and Mitigating DDoS Attacks Using Deep Learning for Online Traffic Analysis.
iSecure Journal, 2024. [PDF]
Under Review
TETRIS: Topology and Energy-aware Joint Task Routing and Offloading for Software-defined Fog Networks.
Submitted to IEEE IoT Journal.
I/O-ETEM: A Lightweight I/O-Based Execution Time Estimation Framework for ML Training Jobs.
Research Experience & Internships
- Worked on FUSE and Kubernetes; resolved concurrency issues in multi-user environments.
- Upcoming research in federated learning and network-aware computing.
- Focused on task offloading using Software Defined Networking (SDN) architectures.
- Research on job scheduling strategies for High Performance Computing (HPC) systems.
- Investigated federated learning frameworks and implementation techniques.
Thesis
Mobility-Aware SDN-Assisted Client Selection in Federated Learning
M.Sc. Thesis, Sharif University of Technology (2024 – Present)
Execution Time Modeling of Data-Intensive Applications
B.Sc. Thesis, Sharif University of Technology (2022)
Skills
- Languages: Persian (native), English (fluent), French (Basic)
- Programming: Python (4+ years), C++ (4+ years), JavaScript (2+ years)
- Tools: Docker, Kubernetes, TensorFlow, PyTorch, Git
- Technologies: SDN, IoT, Federated Learning, HPC
