Rana Khudhair Abbas Ahmed

@ruc.edu.iq

Lecturer/ Computer Engineering Techniques Department /Public Relations Unit
Alrafidain University College

Rana Khudhair Abbas Ahmed


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RANA KHUDHAIR ABBAS AHMED
Permanent Address – Iraq, Baghdad
Contact Number: +9647738601975

Email id: ranazwein@
rana_ruc@


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Rana Khudhair Abbas Ahmed is a Professor and moreover an “Academician by Choice” since Oct 2001.
She has had an outstanding meritorious academic record and is a work product of prestigious systems throughout Alrafidain University College, Iraq, baghdad. She obtained M. Ph.D in Computer Science. Additionally, she has attended One Month Full Time FACULTY TRAINING PROGRAM (FTP) from Alrafidain University College, Iraq.

EDUCATION

 2023: Ph.D Comuter Science (CS) from Alneelain University, Sudan.
 2001: M.Sc. Computer Science (CS) from the Iraqi commission for computers and informatics, Baghdad, , Iraq, 2001. (Now …University of Information Technology & Communications (UITC))
 1997: B.Sc. in Computer science from Baghdad University, College for Pure Science/ Ibn Al-Haitham, Baghdad, Iraq.

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Science Applications
7

Scopus Publications

Scopus Publications

  • IoT-Enabled Technologies for Advancing Renewable Energy Systems
    Yousif Adana Ahmed, Abdul Monem S. Rahma, Wameedh Riyadh Abdulazim, Rana Khudhair Abbas Ahmed, Faris Abdul Kareem Khazal
    International Journal on Informatics Visualization, 2026
    Combining the Internet of Things (IoT) and renewable energy infrastructure has also provided new prospects to make the energy infrastructure more efficient, reliable, and flexible. In the article, the authors consider the contribution of the IoT-enabled architectures to the solar, wind, and hybrid microgrids, with the emphasis on the operational flexibility and performance improvements offered by the real-time monitoring, predictive maintenance, and advanced control algorithms. The systematic process was created with a multi-sensor data collection, edge and cloud computing, and forecasting relying on machine-learning, among different environments and load conditions, to assess system performance. The analysis has evaluated the key performance indices, such as the energy conversion efficiency, stability of grid loads, use of resources, carbon emissions, and reliability in maintenance. The results reveal that the systems being enhanced with IoT are superior to the traditional ones and demonstrate the most prominent changes in the availability of the system, emission minimization, and predictive failure control. The optimization of the energy flow and load shaping with neural network models and time-series prediction proved that intelligent automation is of great importance when managing energy in a distributed system. Such findings demonstrate how IoT can be used to transform renewable energy systems of the future, drawing renewed acceptance to the idea of data-driven technologies in planning over infrastructure. The solution is scalable to support on-site generation of renewable energy and contribute to profound decarbonization through the reduction of intermittency, system outages, and inefficient operation which can be addressed by IoT.
  • Achieving Sustainability in Computing by Minimizing Data Center Carbon Footprints
    Iranian Journal of Information Processing and Management, 2025
  • Harnessing Quantum Computing for Real-Time Data Analytics: A 2025 Perspective
    Iranian Journal of Information Processing and Management, 2025
  • Edutainment as a Concept of Education and Entertainment
    Conference of Open Innovation Association Fruct, 2024
  • Advanced Data Processing in Computer Science: Leveraging MATLAB's Computational Prowess and GUI Capabilities
    Ali Z. Abdulrazzaq, Mina Haider Mohammed, Mohammed Rafid Ahmed Ahmed, Rana Khudhair Abbas Ahmed, Doaa Mohammad Majed, et al.
    Conference of Open Innovation Association Fruct, 2024
    Background: Efficient data processing is an increasing additional important part in computer science, especially with large growing datasets. MATLAB is a complex and most often used tool which is well known for its computational capabilities as it comes with richer library packages than those offered by other simple programming tools, coupled with a fairly robust graphical user interface (GUI). This study exploring the capabilities of MATLAB built-in tools, GUIDE and App Designer, which allow integrating advanced data processing models with user-friendly interfaces.Objective The study aims to assess the capability of MATLAB in mining complex data as well as providing an intuitive interface for users with different levels of programming skills, The aim is to show how MATLAB’s GUI capabilities can be used to significantly simplify real-time data visualization and manipulate of various advanced computation techniques such as neural networks, regression models or multivariate calibration.Methodology: The study researchers created GUIs using MATLAB's GUIDE and App Designer that were hooked up to sophisticated models of computation for data processing. These included neural networks, predictive analytics and real-time data stream processing. The evaluation was done by using these tools on datasets in domains (image processing, and real-time sensor monitoring), based on the performance measurements like throughput speed, accuracy, and user-friendliness.Results: Combining computational modeling of MATLAB with GUI design for complex data tasks extended the accessibility and maneuverability in handling results. Even non-programmable users could effectively communicate with the system, and typical operations performed well model wise, data processing was a real-time thing. The researchers also noted additional avenues for improvement, such as dealing with big-data and integrating upcoming technologies including quantum computing.Conclusion: This feature of MATLAB makes it very user-friendly because computational prowess is combined with GUI development, making it useful for heavy-duty data processing tasks pubs are involved in. The results indicate MATLAB to be a universal tool, allowing for both expert and non-expert users to conduct complex computational problems in a wide range of scientific and industrial domains. It should be improved for more functionality, such as with larger datasets and new technological applications.
  • Contextual Blockchain for the Internet of Things with Dynamic Approach to DLT Based on Ambient Conditions
    Obaida Firas Osama, Abeer Salim Jamil, Amal Faisal Jaffar Al-Madhhachi, Rana Khudhair Abbas Ahmed, Qais Y. Hatim, et al.
    Conference of Open Innovation Association Fruct, 2024
    This article presents a real-time environment aware blockchain framework for the Industrial Internet of Things (IIoT) to optimize contextually blockchain processing and execution. In contrast to current blockchain technologies, which are very static systems, this proposal adapts based on shuttering amounts such as temperature and pressure. The flexibility provided by blockchain promotes data authentication, and its adaptability makes sure that the needs of IIoT environments are met concerning security, integrity, and scalability. The system better accommodates the expanding data loads from IoT sensors and does so more resourcefully by leveraging dynamic block generation, smart contracts, as well as adaptive resource allocation to exploit the available resources serving it at peak performance.The study here also examines how IoT's cybersecurity benefits, in the form of contextual blockchain with cryptographic hashing and zero-knowledge proofs, allow developers to securely embed protection against Distributed Denial of Service (DDoS) attacks alongside data tampering or unauthorized access on an anytime basis. Operational use-cases such as supply chain management, smart cities and edge computing demonstrate the system solution accelerates real-time decision-making, reduces any resource wastage or delays if at all occurring in systemic responses, thereby enhances operational efficiency.In conclusion, contextual blockchain makes scalable and secure as well as flexible solution for IIoT application in which it pertains static nature of other blockchain systems to pragmatic real world situations. This work paves the way for possible future developments such as AI and edge computing integrations, which could make blockchain suitable to run on high-performance environments.
  • Decoding Personal Security - Strategies to Safeguard Humans in the Era of Intelligent Machines
    Akram AbdelBaqi AbdelRahman, Haider Hadi Abbas, Baydaa Taha Rashid Alhamadani, Rana Khudhair Abbas Ahmed, Yahya Majeed, et al.
    Conference of Open Innovation Association Fruct, 2024
    Background: It is estimated that by 2030 more than 60% of the global population will have access to AI-powered applications, suggesting the sweeping adaptation and pervasiveness of AI in our daily lives. Even though this technological progress presents significant opportunities, it is one of the reasons for growing concerns due to its effects on human well-being. As more malevolent cyberattackers leverage AI technology, one of our biggest security risks is the individual.Objective: This article aims to dive into the fusion of AI technology and personal safety by discerning possible cyber threats, that exist in an AI-enabled world and producing numeric approximations of potential risks related to using lethal autonomous weapons. As established in this article, numerous artificial intelligence (AI) technologies are assessed for their vulnerabilities, and it mentions that figures like 90% of human intervention observed during cyberattacks can be seen by running a statistical analysis in databases.Methodology: A systematic review methodology was followed to understand the various defensive techniques. A multidimensional model is proposed for enhancing individual safety based on a comprehensive review of existing methods. This model combines legal environments, technology solutions, and pedagogical practices to create a holistic strategy that tackles the problem from several angles.Results: The prioritization of user empowerment is central in the proposed framework through the incorporation of cybersecurity education. Providing people with the necessary knowledge and skills to protect themselves online is essential in reducing their exposure to AI-driven cyber threats. Guidance is given to individuals, policymakers, and technology companies on how to proactively address security risks linked to artificial intelligence.Conclusion: This article is part of a larger series on the vital discourse surrounding surveillance and security, which includes discussions around recommendations to secure personal information in an AI age. With a focus on legal, technical, and educational mechanisms for good cybersecurity becomes the foundation of going forward that ensures we never sacrifice human well-being in favor of progress.