Ms. Masoumeh Jafari | Network Security | Best Researcher Award
Visiting student, NUS University, Singapore📖
Education Background🎓
Professional Experience🌱
Masoumeh Jafari is an experienced researcher and lecturer in software engineering, actively involved in research and project development related to blockchain, cyber security, machine learning, and IoT. Since 2020, she has served as a research assistant to Dr. Adibnia at Yazd University and collaborated with the Academic and Policy Affairs (APA) Department at Yazd University on initiatives like incident response and threat prevention. Additionally, she has served as a reviewer for prestigious journals, including Information Fusion, Information Sciences, and Soft Computing. She has also judged conference submissions across diverse areas such as IoT, sustainable development, and computer science applications.
Masoumeh’s career spans over 14 years in academia and industry, including roles in game design, blockchain-based projects, and robotics education. Her technical skills encompass languages like Python, Solidity, and C++, with expertise in simulation tools (NS2, CloudSim), big data platforms (Hadoop, Spark), and blockchain environments (Ethereum, Remix).
Research Focus🔬
Masoumeh’s research interests lie in the fields of blockchain technology, cybersecurity, artificial intelligence (AI), and Internet of Things (IoT). She is particularly focused on the practical applications of blockchain in security, healthcare, and smart contracts, exploring new frameworks and solutions for secure, decentralized networks. Her recent projects include blockchain for secure data sharing in IoT systems and deep learning for data analytics.
Author Metrics
Publications Top Notes 📄
- Internet of Things in Eye Diseases: Introducing a New Smart Eyeglasses Designed for Probable Dangerous Pressure Changes in Human Eyes
Authors: G. Prouski, M. Jafari, H. Zarrabi
Conference: IEEE International Conference on Computer and Applications (ICCA)
Year: 2017
Pages: 364-368
Summary: This paper explores the development of innovative smart eyeglasses embedded with IoT sensors to monitor intraocular pressure, aiming to detect and alert users to potentially dangerous pressure fluctuations that could lead to eye diseases such as glaucoma. This solution provides a real-time monitoring system to support early intervention and reduce risks associated with eye pressure changes.
Citations: 13 - Considerations to Spoken Language Recognition for Text-to-Speech Applications
Authors: M.S. Rafieee, S. Jafari, H.S. Ahmadi, M. Jafari
Conference: 2011 UKSim 13th International Conference on Computer Modelling and Simulation
Year: 2011
Summary: This paper discusses the challenges and considerations in spoken language recognition systems used in text-to-speech applications. It evaluates the factors influencing accuracy and proposes methodologies for improving the reliability of language recognition in automated systems.
Citations: 13 - Internet of Things in Eye Diseases Using Smart Glasses
Author: M. Jafari
Journal: International Journal of Engineering Education (IJEE)
Year: 2017
Pages: 1034-1042
Summary: Building on IoT applications in healthcare, this paper presents the design and functionality of smart glasses aimed at diagnosing and managing eye diseases. The paper elaborates on sensor technology, data transmission, and potential benefits for patients with chronic eye conditions, contributing to personalized medical solutions and preventive care.
Citations: 2 - A Novel Method for Extracting Blood Vessels in Digital Retinal Images
Author: M. Jafari
Journal: Soft Computing Journal
Volume: 10, Issue 1
Year: 2021
Pages: 110-121
Summary: This paper introduces a new algorithm for extracting blood vessels in retinal images, which is a crucial step for diagnosing various eye diseases. Utilizing soft computing techniques, the method enhances image segmentation and detection accuracy in digital retinal imaging, improving diagnosis and facilitating automated eye health monitoring.
Citations: 1 (recently cited) - Isolation of Vessels in Retinal Color Images
Author: M. Jafari
Journal: Soft Computing Journal
Year: 2022
Summary: This publication presents advanced techniques for isolating blood vessels in retinal color images, essential for retinal disease detection and analysis. The study leverages soft computing and image processing methods to improve the clarity and precision of vessel isolation in complex retinal imaging scenarios.