Bogdan-Constantin Neagu | Power Systems | Best Researcher Award

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Assoc Prof Dr. Bogdan-Constantin Neagu | Power Systems | Best Researcher Award

Director of CEREM Department at Gheorghe Asachi Technical University of Iasi, Romania

Summary:

Assoc. Prof. Dr. Bogdan-Constantin Neagu is an accomplished academic and researcher in the field of electrical engineering. Currently an Associate Professor at “Gheorghe Asachi” Technical University of Iasi, Romania, he specializes in power transmission and distribution, energy systems planning, and smart grid technologies. Dr. Neagu holds a PhD in Electrical Engineering from the same university, where his research focused on optimizing electric energy distribution systems. With extensive teaching experience since 2009, he has guided numerous students through courses, dissertations, and research projects. His work includes contributions to academic research through grants, contracts, and publications, further establishing his expertise in energy systems.

Profile:

Education:

Assoc. Prof. Dr. Bogdan-Constantin Neagu has a strong academic foundation in electrical engineering. He earned his PhD in Electrical Engineering from “Gheorghe Asachi” Technical University of Iasi, Romania, with a thesis focused on optimizing the structure and steady-state of electric energy repartition and distribution systems. Dr. Neagu also holds a Master of Science in Power System Management from the same institution, where he explored power flow optimization in power distribution systems. His academic journey began with a Bachelor’s degree in Power Engineering from “Gheorghe Asachi” Technical University, where he gained in-depth knowledge of power distribution network analysis. His education has equipped him with advanced expertise in transmission, distribution, and optimization of electrical systems.

Professional Experience:

Assoc. Prof. Dr. Bogdan-Constantin Neagu has a distinguished professional background in electrical engineering, with over a decade of academic and research experience. He began his career as a University Tutor at the “Gheorghe Asachi” Technical University of Iasi, Romania, in 2009, where he contributed to teaching and research in power distribution and energy systems. He advanced to Assistant Professor in 2011 and later to Senior Lecturer in 2014, focusing on courses such as Transmission and Distribution of Electric Energy and Distribution Systems Planning Strategy. Since 2022, he has been serving as an Associate Professor, continuing to teach, supervise student research, coordinate theses, and contribute to academic committees. Dr. Neagu’s professional experience is marked by significant involvement in academic research, supported by grants, contracts, and publications, as well as his active participation in the academic and research community through student mentorship and innovative research in energy systems.

Research Interests:

Assoc. Prof. Dr. Bogdan-Constantin Neagu’s research interests are focused on optimizing electrical energy systems, with particular attention to the transmission and distribution of electric energy. His research has explored areas such as smart metering implementation, the optimization of power distribution networks, and the steady-state analysis of energy systems. He has contributed to developing innovative strategies for the integration of real-time data from SCADA systems and smart metering into the optimization of distribution network configurations. Additionally, Dr. Neagu is involved in research related to energy market policies, protection and automation systems, and the monitoring and diagnostics of electrical equipment. His work bridges theoretical advancements and practical applications, aiming to enhance the efficiency and reliability of power systems.

Skills:

Assoc. Prof. Dr. Bogdan-Constantin Neagu possesses a wide range of skills that contribute to his expertise in electrical engineering and academia. His technical skills include advanced proficiency in analyzing and designing electric energy transmission and distribution systems, as well as the steady-state optimization of power networks. He has extensive experience with specialized software like DIGSilent Power Factory, Neplan, and EDSA, and has developed his own software for power system analysis. In addition, he is skilled in programming languages such as C++ and Matlab. Dr. Neagu’s organizational and managerial abilities are reflected in his capacity for innovation, time management, multitasking, and budget management. He demonstrates strong leadership in team coordination and critical thinking. His communication skills are exemplary, enabling effective teaching, research collaboration, and student mentorship. Furthermore, Dr. Neagu is proficient in English and French, and he possesses high adaptability to new environments and technologies, critical for his work in research contracts and scientific article reviews for international ISI journals.

Concution:

Assoc. Prof. Dr. Bogdan-Constantin Neagu’s extensive teaching experience, strong educational background, significant research contributions, and exceptional communication and organizational skills make him a highly suitable candidate for the Best Researcher Award. His commitment to advancing electrical engineering through education and research positions him as an exemplary figure in the academic community.

Publication Top Noted:

Face spoofing, age, gender and facial expression recognition using advance neural network architecture-based biometric system

  • Authors: S. Kumar, S. Rani, A. Jain, C. Verma, M.S. Raboaca, Z. Illés, B.C. Neagu
  • Journal: Sensors
  • Year: 2022
  • Volume: 22(14)
  • Article: 5160
  • Citations: 83

Phase load balancing in low voltage distribution networks using metaheuristic algorithms

  • Authors: O. Ivanov, B.C. Neagu, M. Gavrilas, G. Grigoras, C.V. Sfintes
  • Conference: 2019 International Conference on Electromechanical and Energy Systems (SIELMEN)
  • Year: 2019
  • Pages: 1-6
  • Citations: 34

Optimal phase load balancing in low voltage distribution networks using a smart meter data-based algorithm

  • Authors: G. Grigoras, B.C. Neagu, M. Gavrilas, I. Tristiu, C. Bulac
  • Journal: Mathematics
  • Year: 2020
  • Volume: 8(4)
  • Article: 549
  • Citations: 32

A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

  • Authors: B.C. Neagu, O. Ivanov, G. Grigoras, M. Gavrilas
  • Journal: Mathematics
  • Year: 2020
  • Volume: 8(2)
  • Article: 235
  • Citations: 32

Optimized sizing of energy management system for off-grid hybrid solar/wind/battery/biogasifier/diesel microgrid system

  • Authors: A.M. Jasim, B.H. Jasim, F.C. Baiceanu, B.C. Neagu
  • Journal: Mathematics
  • Year: 2023
  • Volume: 11(5)
  • Article: 1248
  • Citations: 31

Smart Meter Data-based three-stage algorithm to calculate power and energy losses in low voltage distribution networks

  • Authors: G. Grigoras, B.C. Neagu
  • Journal: Energies
  • Year: 2019
  • Volume: 12(15)
  • Article: 3008
  • Citations: 31

An efficient peer-to-peer based blockchain approach for prosumers energy trading in microgrids

  • Authors: B.C. Neagu, G. Grigoras, O. Ivanov
  • Conference: 2019 8th International Conference on Modern Power Systems (MPS)
  • Year: 2019
  • Pages: 1-4
  • Citations: 31

Efficient optimization algorithm-based demand-side management program for smart grid residential load

  • Authors: A.M. Jasim, B.H. Jasim, B.C. Neagu, B.N. Alhasnawi
  • Journal: Axioms
  • Year: 2022
  • Volume: 12(1)
  • Article: 33
  • Citations: 28

GeFL: Gradient Encryption-Aided Privacy Preserved Federated Learning for Autonomous Vehicles

  • Authors: R. Parekh, N. Patel, R. Gupta, N.K. Jadav, S. Tanwar, A. Alharbi, A. Tolba, B.C. Neagu
  • Journal: IEEE Access
  • Year: 2023
  • Volume: 11
  • Pages: 1825-1839
  • Citations: 26

Elson Cibaku | Power Systems | Best Researcher Award

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Mr. Elson Cibaku | Power Systems | Best Researcher Award

Elson Cibaku at New Jersey Institute of Technology, United States

Summary:

Mr. Elson Cibaku is a dedicated researcher and PhD candidate in Industrial Engineering at the New Jersey Institute of Technology (NJIT), maintaining a perfect GPA of 4.0. He holds both a MSc and a BSc in Computer Science from the University of Tirana, Albania. At NJIT, Mr. Cibaku contributes to groundbreaking research in power systems, vaccine distribution, and optimization problems through advanced machine learning and deep learning methodologies, resulting in several impactful publications. His professional experience includes a role as Lead Software Engineer at Impala Digital in Tirana, Albania, where he significantly improved system performance and led the adoption of advanced technologies. Prior to that, he was a Senior Software Engineer at Facilization, where he led critical projects and received the Innovation Award in 2018 for his outstanding contributions to software development. Mr. Cibaku has also served as a lecturer at the University of Tirana, where he taught various computer science courses and engaged in collaborative research. Proficient in multiple programming languages and advanced technologies, Mr. Cibaku’s skills span machine learning, data processing, web development, and cloud services. His certifications include SQL business intelligence development and data modeling. Mr. Cibaku’s extensive academic and professional background highlights his expertise and commitment to advancing technology and data science.

Profile:

Education:

Mr. Elson Cibaku is currently pursuing a PhD in Industrial Engineering at the New Jersey Institute of Technology (NJIT), where he has achieved a perfect GPA of 4.0. His PhD coursework includes advanced topics such as Stochastic Programming, Machine Learning, Deep Learning, Reinforcement Learning, Statistical Methods in Data Science, Optimization Techniques for Data Engineering, Advanced Topics in Operations Research, Data Mining, and Supply Chain Engineering. Prior to his doctoral studies, he earned a MSc in Computer Science from the University of Tirana, Albania, with coursework in Parallel Programming, Coding Theory and Cryptographies, Advanced Operating Systems, Algorithmic, Object-Oriented Programming, Software Engineering, and Artificial Intelligence. Mr. Cibaku also holds a BSc in Computer Science from the University of Tirana, where he laid the foundation for his technical expertise and research skills.

Professional Experience:

Mr. Elson Cibaku has amassed extensive professional experience in both academic and industry settings. Currently, he serves as a Research Assistant at the New Jersey Institute of Technology (NJIT), where he collaborates on cutting-edge research projects, resulting in impactful papers on topics such as power systems, vaccine distribution, and optimization problems. From September 2021 to May 2023, he also worked as a Teaching Assistant at NJIT, where he developed instructional materials and conducted grading and assessment activities for various engineering courses. Prior to his time at NJIT, Mr. Cibaku was a Lead Software Engineer at Impala Digital in Tirana, Albania, from February 2021 to August 2021. In this role, he orchestrated tech stack adoption, led cross-functional teams, and developed a C# cache library that significantly improved system performance. Before that, he served as a Senior Software Engineer at Facilization from September 2013 to February 2021, where he led critical projects, such as developing a scalable backend for Virtual IBAN and optimizing SQL queries for the Bank of Albania’s Credit Registry, earning the Innovation Award in 2018. Additionally, Mr. Cibaku has experience as a Lecturer at the University of Tirana from October 2016 to August 2021, where he taught various computer science courses and supervised master and undergraduate students. His diverse professional background highlights his expertise in software engineering, research, and teaching, underscoring his commitment to advancing technology and data science.

Research Interests:

Mr. Elson Cibaku’s research interests lie at the intersection of industrial engineering, computer science, and data science. His current research focuses on leveraging advanced machine learning and deep learning methodologies to enhance efficiency in power systems, optimize vaccine distribution, and solve complex multi-pickup and delivery problems. He is particularly interested in the applications of graph attention networks, distributed optimization, and reinforcement learning in these domains. Additionally, Mr. Cibaku’s work encompasses statistical methods in data science, stochastic programming, optimization techniques for data engineering, and advanced topics in operations research. His diverse research portfolio reflects a strong commitment to addressing real-world challenges through innovative technological solutions.

Skills:

Mr. Elson Cibaku possesses a diverse and comprehensive skill set, underpinned by his proficiency in multiple programming languages including Python, C#, and Java. His expertise in machine learning spans supervised learning (regression and classification), deep learning (neural networks, transformers, generative models, transfer learning, and NLP models), unsupervised learning (clustering, dimensionality reduction, and anomaly detection), reinforcement learning (policy gradient methods, deep Q-learning, PPO, and TD learning), and generative adversarial networks. In data processing and visualization, Mr. Cibaku is adept with tools such as Tableau, Matplotlib, Looker Studio, and Power BI. His knowledge in data technologies encompasses data mining, the big data life cycle, Google Big Query, data warehousing, and data structures. In the realm of web development, he is skilled in .NET Core, ASP.NET Web API, and CQRS. His database management capabilities include working with relational databases (SQL Server, Oracle Database, and PostgreSQL), indexing strategies, data modeling, performance tuning, optimization, and NoSQL databases (MongoDB). Additionally, he is proficient in cloud services such as Microsoft Azure, Google Cloud Platform, and Amazon Web Services, and has experience with application servers including Keycloak, WildFly, NGINX, and Microsoft IIS. Other tools in his repertoire include Redis and DevExpress XAF. Mr. Cibaku holds several certifications, including MCSA: SQL 2016 Business Intelligence Development, MCPS: Microsoft Certified Professional, and certifications in implementing and developing data warehouses with Microsoft SQL Server. This extensive skill set positions him as a versatile and knowledgeable professional in the fields of computer science and data engineering.

Publications:

Boosting Efficiency in State Estimation of Power Systems by Leveraging Attention Mechanism

  • Authors: E. Cibaku, F. Gama, S. W. Park
  • Journal: Energy and AI
  • Volume: 16
  • Article Number: 100369