Contact Dr Mennan Guder
- Email: Mennan.Guder@cranfield.ac.uk
Background
Mennan Guder is a dedicated research fellow currently engaged in the PRIME project, where he leverages his expertise in machine learning and agent-based modeling to derive meaningful insights from complex datasets. In this collaborative role, Mennan actively collaborates with fellow researchers from various universities, contributing to the advancement of knowledge in his field.
With a strong educational foundation, Mennan holds a Bachelor of Science degree in Computer Engineering, a Master of Science degree in Data Mining, and a Doctor of Philosophy degree in Deep Learning. His academic journey is complemented by a minor in mathematics, reflecting his comprehensive approach to problem-solving.
During his impressive 17-year tenure at the National Scientific Council of Turkey, Mennan served as a versatile professional, excelling as a system architect and applied researcher. His impactful contributions spanned diverse domains, including power distribution, avionics, cybersecurity, distributed systems, and mission-critical systems. Mennan's work not only showcased technical prowess but also demonstrated a keen ability to navigate complex technological landscapes and provide innovative solutions.
Mennan's technical proficiency encompasses a wide array of technologies, including Java, Java EE, C, C++, Spring, Spring Boot, ReactJS, and databases such as Oracle and PostgreSQL. Beyond coding, he has gained substantial knowledge in agile methodologies, continuous integration/continuous deployment (CI/CD) pipelines, Git version control, and collaboration tools like Jira and Confluence. His multidimensional skill set is further enriched by a deep understanding of machine learning, reflecting his commitment to staying at the forefront of emerging technologies.
In addition to his academic and professional accomplishments, Mennan's commitment to collaborative research and technological innovation positions him as a valuable contributor to the dynamic field of machine learning and data analysis. His diverse experiences and skills underscore a passion for addressing complex challenges, making him a valuable asset to the research community.
Research opportunities
My research interests revolve around the convergence of energy digitization, energy policy simulation, and advanced data analytics, with a focus on the following key areas:
Energy Digitization:
Exploring the integration of digital technologies to enhance energy systems, with a particular emphasis on improving efficiency, reliability, and sustainability.
Energy Policy Simulation:
Investigating the development and application of simulation models to assess the impact of energy policies on system dynamics, resource allocation, and environmental outcomes.
Distribution and Transmission Power Quality Analysis:
Analyzing the quality of power distribution and transmission to identify and mitigate issues related to voltage variations, harmonics, and reliability in electrical networks.
Artificial Intelligence for Decarbonization:
Leveraging artificial intelligence techniques to optimize energy systems and facilitate their transition to low-carbon alternatives, aiming to reduce carbon emissions and promote sustainable energy practices.
Demand Analysis:
Investigating patterns and factors influencing energy demand to inform efficient resource allocation and support the development of responsive energy systems.
Electrical Vehicle Charging:
Exploring strategies for intelligent and efficient electrical vehicle charging, addressing issues related to infrastructure, grid impact, and user behavior.
Data Fusion, Federation, and Automation:
Researching techniques for integrating, federating, and automating data processes, with a focus on enhancing the interoperability and efficiency of energy systems.
Data Analysis for Cybersecurity:
Applying data analysis methods to enhance cybersecurity measures within energy systems, ensuring the integrity and resilience of critical infrastructure.
Cryptology Applications in Military Systems:
Investigating the applications of cryptology in military systems, with a focus on ensuring secure communication and data protection in defense contexts.
These research interests collectively aim to contribute to the advancement of energy systems, policy development, and data analytics, fostering resilient, efficient, and secure energy landscapes.
Current activities
I am actively contributing to cutting-edge research as a Research Fellow at 美姬阁, deeply immersed in the Protecting Minority Ethnic Communities Online (PRIME) project. My research spans several pivotal aspects, including energy digitization, data security, data service federation, energy consumption analysis, and the exploration of large language models. In the dynamic field of energy resilience and sustainability, my work involves the development and application of advanced technologies to enhance the efficiency, security, and analysis of energy systems. This multifaceted research role aligns seamlessly with my commitment to addressing contemporary challenges in energy digitization while ensuring data security and leveraging innovative approaches for enhanced energy consumption analysis.
In addition to my role at 美姬阁, I extend my research efforts by providing data mining applications for the cybersecurity course at Bilge University and Karadeniz Teknik University. This outreach reflects my dedication to disseminating knowledge and contributing to the broader academic community, further enriching my research pursuits and fostering collaborative initiatives in the realm of energy resilience and cybersecurity.
