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Dr. Reza Fotohi | Security and Privacy | Best Researcher Award

PhD Candidate, SBU, Iran

Reza Fotohi is an accomplished researcher in computer software engineering, with a strong academic background and numerous contributions to the field. He earned his Ph.D. from Shahid Beheshti University, Tehran, Iran, where his research focused on privacy-preserving data models in intelligent enterprises. Recognized globally, Fotohi is amongst the top 2% of researchers in the world according to Stanford University. His work spans advanced software engineering, network security, and ultra-large-scale systems.

Education 🎓

Reza Fotohi completed his Ph.D. in Computer Software Engineering at Shahid Beheshti University (SBU) from September 2019 to September 2023. His coursework included Advanced Software Engineering, Self-adapting and Self-organizing Systems, Advanced Network Security, and Ultra Large Scale Systems, achieving a GPA of 19.0/20. Fotohi served as a Teaching Assistant for Ultra Large Scale Systems in 2021 and 2022, and as a Research Assistant in 2022. His thesis, supervised by Dr. Fereidoon Shams Aliee and advised by Dr. Bahar Farahani, focused on developing a lightweight model for privacy-preserving data in intelligent enterprises.

Experience đź’Ľ

Reza Fotohi has extensive teaching experience, having taught various computer engineering and information technology courses at several universities in Iran. He taught Applied Computer Skills at Shahid Beheshti University, and Computer Networks, Network Programming, Information Technology, and E-commerce at the University of Applied Science and Technology (UAST). Additionally, he taught courses including Internet Engineering, Algorithm Design, Data Structure, and Software Engineering at Payame Noor University (PNU) and Islamic Azad University (IAU).

Research Interests 🔬

Fotohi’s research interests lie in advanced software engineering, network security, and privacy-preserving data systems. He is particularly focused on self-adapting and self-organizing systems, ultra-large-scale systems, and the application of blockchain technology in securing communications between IoT devices. His work also encompasses big data-aware intrusion detection systems, network-layer attack discovery, and performance-aware placement in virtualized network functions.

Awards 🏆

Reza Fotohi has received numerous accolades throughout his academic career. During his Ph.D., he was recognized as one of the top 2% of researchers worldwide by Stanford University. He was awarded a fellowship by the Faculty of Computer Science and Engineering at Shahid Beheshti University and was selected to use the facilities of the National Elite Foundation. Fotohi ranked 17th nationwide in the Ph.D. university entrance exam and consistently ranked among the top students during his undergraduate and postgraduate studies.

Publications Top Notesđź“š

  1. A Crisis‑driven e‑Learning Capability Maturity Model in the Age of COVID‑19: Process‑based Maturity Assessment (2021), National Conference on Advances in Enterprise Architecture. Link
    • Cited by: Articles on e-learning models during crises.
  2. Big Data‑aware Intrusion Detection System in Communication Networks: A Deep Learning Approach (2021), Journal of Grid Computing. Link
    • Cited by: Research on big data and intrusion detection systems.
  3. A reliable and secure method for network‑layer attack discovery and elimination in mobile ad‑hoc networks based on a probabilistic threshold (2021), Security and Privacy. Link
    • Cited by: Studies on network security in mobile ad-hoc networks.
  4. Securing Communication between Things using Blockchain Technology based on Authentication and SHA‑256 to Improving Scalability in Large‑Scale IoT (2021), Computer Networks. Link
    • Cited by: Research on blockchain applications in IoT.
  5. Defense against flooding attacks using probabilistic thresholds in the internet of things ecosystem (2021), Security and Privacy. Link
    • Cited by: Works on IoT security mechanisms.
Reza Fotohi | Security and Privacy | Best Researcher Award

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