Madalin Costin | Energy | Best Researcher Award

Mr. Madalin Costin | Energy | Best Researcher Award

Lecturer at Lower Danube” University of Galati, Romania

Madalin Costin is an accomplished academic and researcher with a strong foundation in Electrical Engineering. He specializes in electric drives, renewable energy systems, and the use of advanced control strategies for electromagnetic energy conversion processes. Currently a lecturer at “Dunarea de Jos” University of Galati, Romania, Madalin has consistently demonstrated a passion for teaching and research. His work spans both theoretical and applied aspects of energy efficiency and control systems, with a particular focus on improving performance through innovative methods. His ongoing projects, such as the evaluation of novel control strategies for PMSM motors, highlight his commitment to advancing the field. As a multilingual academic, Madalin is well-positioned to engage in international collaborations, furthering the impact of his research.

Professional Profile

Education

Madalin Costin holds a robust academic background in Electrical Engineering, starting with his undergraduate degree from “Dunarea de Jos” University of Galati in Romania, where he specialized in Electric Drives. He continued his education with a Master’s degree in Electrical Engineering, focusing on the Rational Use of Energy and Renewable Sources. Furthering his expertise, he completed his PhD at the same institution, where his research focused on energy-efficient control strategies. Currently, Madalin is pursuing a second PhD at Gheorghe Asachi Technical University of Iasi, demonstrating his commitment to continued academic growth.

Professional Experience

Madalin Costin has accumulated valuable professional experience, beginning his career as a Computer Scientist at “Dunarea de Jos” University of Galati. Over the years, he progressed to Assistant and then Lecturer positions, where he has been responsible for teaching both theoretical and practical aspects of Electrical Engineering. His experience in academic settings is complemented by his involvement in project management. As of June 2024, he is managing a significant research project focused on evaluating a novel control strategy for electromagnetic energy conversion. His professional journey reflects his evolving expertise and leadership in both academia and research.

Research Interests

Madalin Costin’s research interests are primarily focused on renewable energy systems, electric drives, and advanced control strategies for electromagnetic energy conversion. He has a strong interest in improving the efficiency of electric motors and developing new control methods that are both energy-efficient and adaptable to real-world applications. His ongoing work on Radial Basis Function Neural Networks (RBF-NN) and Model Predictive Control (MPC) for Permanent Magnet Synchronous Motors (PMSM) is aimed at optimizing energy conversion processes. He is particularly interested in how these technologies can be applied to renewable energy sources and contribute to more sustainable engineering solutions.

Research Skills

Madalin Costin is proficient in a variety of research skills related to electrical engineering and renewable energy. His expertise includes control theory, energy efficiency, and optimization techniques, particularly in the context of electric drives and renewable systems. He is skilled in using advanced computational methods, including neural networks and predictive control algorithms, to model and optimize energy systems. Madalin also possesses solid skills in project management, demonstrating an ability to lead and coordinate complex research initiatives. Additionally, his proficiency in academic writing and presenting research ensures that his work reaches both scientific and industrial audiences.

Awards and Honors

While Madalin Costin’s career is still in its developing stages, he has already shown significant promise in both his academic and research pursuits. His work on energy efficiency and control strategies for electric drives has been recognized within his university and research community. He is an active participant in various academic conferences and workshops, where his research is often acknowledged. His ongoing contributions to research on renewable energy systems, particularly in the context of electromagnetic energy conversion, are likely to garner more formal recognition as his research advances and his academic portfolio expands.

Conclusion

Madalin Costin is a highly capable and dedicated researcher with a strong academic foundation, a focus on renewable energy and advanced control strategies, and a steady record in teaching and project management. His current research and his approach to advanced energy systems place him in a strong position for the Best Researcher Award. By increasing his publication output, expanding industry collaborations, and exploring additional research areas, he could further elevate his impact and recognition in the academic and research community.

Publication Top Notes

  1. Induction Motor Improved Vector Control Using Predictive and Model-Free Algorithms Together with Homotopy-Based Feedback Linearization
    • Authors: Costin, M., Lazar, C.
    • Year: 2024
    • Journal: Energies, 17(4), 875
  2. Field-Oriented Predictive Control Structure for Synchronous Reluctance Motors
    • Authors: Costin, M., Lazar, C.
    • Year: 2023
    • Journal: Machines, 11(7), 682
    • Citations: 5
  3. Thermal Regime of Induction Motors After Rewinding for Other Characteristics Than Those Established by Design
    • Authors: Voncila, I., Selim, E., Paraschiv, I., Costin, M.
    • Year: 2023
    • Conference: 8th International Symposium on Electrical and Electronics Engineering, ISEEE 2023 – Proceedings
  4. Constrained Predictive Current Control in dq Frame for a Permanent Magnet Synchronous Machine
    • Authors: Costin, M., Lazar, C.
    • Year: 2023
    • Conference: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023
  5. Comparative Study of Predictive Current Control Structures for a Synchronous Reluctance Machine
    • Authors: Costin, M., Lazar, C.
    • Year: 2022
    • Conference: 26th International Conference on System Theory, Control and Computing, ICSTCC 2022 – Proceedings
    • Citations: 1
  6. Predictive Control of a Two-Input Two-Output Current System for Permanent Magnet Synchronous Machines
    • Authors: Costin, M., Lazar, C.
    • Year: 2021
    • Conference: 25th International Conference on Methods and Models in Automation and Robotics, MMAR 2021
    • Citations: 1
  7. The Influence of Saturation on the Performance of PMSM
    • Authors: Voncila, I., Paraschiv, I., Costin, M.
    • Year: 2021
    • Conference: ISEEE 2021: 7th International Symposium on Electrical and Electronics Engineering
  8. Predictive dq Current Control of an Induction Motor
    • Authors: Costin, M., Lazar, C.
    • Year: 2021
    • Conference: 25th International Conference on System Theory, Control and Computing, ICSTCC 2021
    • Citations: 1
  9. Active Flux Based Predictive Control of Interior Permanent Magnet Synchronous Machine
    • Authors: Costin, M., Lazar, C.
    • Year: 2020
    • Conference: International Symposium on Fundamentals of Electrical Engineering, ISFEE 2020
    • Citations: 1
  10. Evaluation of PV Panels by a Spline-Fuzzy Approximation and Classification Method
    • Authors: Costin, M., Bivol, I., Voncila, I.
    • Year: 2018
    • Conference: International Symposium on Fundamentals of Electrical Engineering, ISFEE 2018

 

Saeed Shahrokhian | Energy | Best Researcher Award

Prof Dr. Saeed Shahrokhian | Energy | Best Researcher Award

Academic Staff, Sharif University of Technology, Iran

Dr. Saeed Shahrokhian is a highly accomplished professor in the Department of Chemistry at Sharif University of Technology (SUT), Tehran, Iran. With a distinguished academic background including a Ph.D. from Isfahan University, he has been a key figure at SUT since 2000, progressing from Assistant to Full Professor. His research focuses on the design and application of chemically modified electrodes, nanostructured materials, electrochemical energy storage devices, and biosensors for cancer biomarker detection. Dr. Shahrokhian has received numerous accolades, including the Superior Educational Master and Distinguished Researcher awards from SUT, as well as recognition from Iran’s Ministry of Science. His research excellence is reflected in his impressive H-index of 62 and inclusion among the top 1% of highly cited international scientists. With a vast body of published work and ongoing contributions to cutting-edge electrochemical research, Dr. Shahrokhian stands out as a strong candidate for the Research for Best Researcher Award.

Profile

Education

Dr. Saeed Shahrokhian has an impressive educational background that has greatly shaped his career in chemistry. He earned his B.Sc. in Chemistry from Isfahan University in 1990, followed by his M.Sc. from the same institution in 1994. Dr. Shahrokhian completed his Ph.D. at Isfahan University in 1999, where his research laid the foundation for his future contributions to analytical chemistry. His academic journey was marked by rigorous study and a focus on developing innovative approaches to chemical sensors and electrochemical energy conversion. His deep understanding of chemistry, combined with his commitment to research excellence, has contributed significantly to his esteemed career as a professor at Sharif University of Technology. This robust academic background provided Dr. Shahrokhian with the tools and knowledge to become a leading expert in his field, contributing to advancements in nanostructured materials, biosensors, and electrochemical systems.

Professional Experience

Dr. Saeed Shahrokhian is a Full Professor in the Department of Chemistry at Sharif University of Technology, where he has held positions since 2000. His professional journey began as an Assistant Professor from 2000 to 2004, followed by an Associate Professor role until 2008. Since June 2008, he has served as a Full Professor, reflecting his sustained excellence in academic research and teaching. Dr. Shahrokhian’s expertise spans electrochemistry, with a focus on the design, construction, and application of chemically modified electrodes, nano-structured materials, and electrochemical energy conversion devices. He has made significant contributions to capacitive deionization and the development of electrochemical biosensors for cancer biomarkers and pathogenic bacteria. His work is recognized globally, as evidenced by his numerous awards, including being named a highly cited researcher by ISI and Scopus. His professional experience highlights his leadership in advancing scientific knowledge and innovation in the field of chemistry.

Research Interests

Dr. Saeed Shahrokhian’s research interests lie at the intersection of electrochemistry, materials science, and biosensors. His work primarily focuses on the design, construction, and application of chemically modified electrodes (CMEs), with an emphasis on leveraging nano-structured materials to enhance electrode performance. He is particularly interested in electrochemical energy conversion and storage devices, capacitive deionization, and the development of aptamer-based electrochemical biosensors for detecting cancer biomarkers and pathogenic bacteria. Additionally, Dr. Shahrokhian explores the application of nanocomposite materials for surface modification of electrodes, especially in electrocatalytic water splitting, and carrier-based potentiometric ion sensors. His research contributes significantly to the advancement of analytical techniques, fostering innovations that have broad implications in environmental monitoring, healthcare, and energy storage systems. Dr. Shahrokhian’s diverse research portfolio reflects his commitment to addressing both fundamental scientific questions and practical challenges through interdisciplinary approaches.

Research Skills

Dr. Saeed Shahrokhian, a highly accomplished researcher at the Department of Chemistry, Sharif University of Technology, exhibits exceptional research skills in the realm of electrochemical sciences. His expertise lies in the design and development of chemically modified electrodes (CMEs), with a focus on applying nanostructured materials to enhance electrochemical energy conversion and storage devices. His proficiency in capacitive deionization, coupled with his innovative work in aptamer-based electrochemical biosensors for cancer biomarkers and pathogenic bacteria detection, showcases his interdisciplinary approach. Additionally, Dr. Shahrokhian’s skill in the development of nanocomposite materials for surface modification of electrodes in electrocatalytic water splitting further highlights his contributions to sustainable energy solutions. His extensive knowledge in potentiometric ion sensors and his ability to integrate cutting-edge technologies into practical applications reinforce his status as a leading researcher. These advanced research skills make him a strong candidate for the Research for Best Researcher Award.

Awards and Honors

Dr. Saeed Shahrokhian, a highly accomplished researcher from the Department of Chemistry at Sharif University of Technology, has earned numerous prestigious awards and honors throughout his career. He has been recognized as the Distinguished Researcher of the Chemistry Department multiple times, including in 2004, 2008, 2014, and 2020. In addition, Dr. Shahrokhian was named Superior Educational Master for various academic years, such as 2003-2004, 2010-2011, and 2014-2015. His significant contributions to science have also been acknowledged at the national level, as he was named Distinguished Researcher in Basic Science by the Ministry of Science, Research, and Technology in 2012. Notably, he is a 1% Highly Cited International Scientist (ISI Web of Knowledge, 2012-2024) and a 2% Highly Cited Scientist (Scopus, 2021-2024). His extensive research and influence in the field have led him to be a Highly Cited Researcher at Sharif University in both 2017 and 2022.

Adel Oulefki | Energy Efficiency | Environmental Engineering Impact Award

Dr. Adel Oulefki | Energy Efficiency | Environmental Engineering Impact Award 

RISE at University of Sharjah, United Arab Emirates.

Dr. Adel Oulefki is a distinguished researcher with a Ph.D. in Computer Science and honors from the University of Bordj Bou Arréridj, Algeria, and an HDR accreditation from IGEE. His academic and professional journey includes significant roles at the Centre de Développement des Technologies Avancées (CDTA) and the University of Sharjah, focusing on computer science and engineering applications in medical, environmental, and security fields. His expertise spans signal and image analysis, data clustering, and pattern recognition. Dr. Oulefki has led innovative projects such as developing algorithms for lung tumor analysis and COVID-19 visualization using virtual reality. His work, recognized with awards like the Best Scientific Work on COVID-19, showcases his contributions to environmental health and waste management through advanced technology. His scholarly output includes numerous publications in prestigious journals and contributions to international conferences.

Profile
Education

Dr. Adel Oulefki holds an extensive academic background with degrees that underline his expertise in electrical engineering and computer science. He earned his Bachelor’s degree in Industrial Computing from the University of Bordj Bou Arréridj in 2007, where he focused on implementing VHDL designs on FPGA. He continued his studies at the same institution, achieving a Master’s degree in Electrical Engineering in 2009, with a thesis on voice codec implementation. Dr. Oulefki completed his Ph.D. in Computer Science at the University of Bordj Bou Arréridj in 2014, with research centered on real-time video classification. In 2018, he obtained an HDR (Habilitation à Diriger des Recherches) from the Institute of Electrical Engineering and Electronics (IGEE), enabling him to supervise research and further his academic contributions. His educational journey underscores his commitment to advancing knowledge in his field.

Professional Experience

Dr. Adel Oulefki has a distinguished career in research and academia, with a Ph.D. in Computer Science from the University of Bordj Bou Arréridj, Algeria, and a habilitation degree from IGEE. Since 2016, he has been a senior researcher at the Centre de Développement des Technologies Avancées (CDTA), leading significant projects in machine vision and image processing. His roles include Research Director at CDTA, where he supervised Ph.D. students and led research on algorithms for lung tumor analysis. Currently, as a Postdoctoral Research Fellow at the University of Sharjah, he focuses on smart buildings and digital twins technology. Dr. Oulefki’s previous positions include Fulbright Visiting Scholar at CUNY, a Scientific Council member at CDTA, and various roles in teaching and research across multiple institutions, including a visiting scholar stint at Università degli Studi di Trento.

Research Interest

Dr. Adel Oulefki’s research interests are primarily at the intersection of computer science and engineering, focusing on applications in medical, environmental, and agronomic fields. He specializes in signal, image, and video analysis, leveraging advanced techniques in data clustering and pattern recognition. His work includes developing algorithms for image recognition and processing, with notable contributions to medical imaging and environmental monitoring. Dr. Oulefki is particularly engaged in projects related to smart buildings and smart cities, utilizing Digital Twins technology for urban innovation. His research also addresses critical environmental challenges, such as COVID-19 impact analysis and oil spill detection through thermal imagery. With a strong emphasis on applied research, Dr. Oulefki’s projects frequently involve collaborations across disciplines and institutions, aiming to enhance both technological capabilities and practical solutions in various sectors.

Research Skills

Dr. Adel Oulefki possesses a diverse and robust skill set in research, particularly within the domains of signal, image, and video analysis. His expertise in developing advanced algorithms for image recognition and processing, as well as his proficiency in data clustering and pattern recognition using RGB cameras and thermal sensors, underscores his strong technical capabilities. Dr. Oulefki’s skills extend to applied research in smart buildings and smart cities, leveraging Digital Twins technology to enhance urban living. He is adept at supervising Ph.D. students and managing research projects, including the development of innovative solutions for lung tumor analysis and COVID-19 visualization. His command of various programming languages and software tools, such as MATLAB and Python, complements his analytical prowess, enabling him to tackle complex research problems and contribute to significant advancements in his field. Dr. Oulefki’s ability to bridge theoretical concepts with practical applications demonstrates his comprehensive research acumen.

Awards and Recognition

Dr. Oulefki has received several prestigious awards and recognitions, including the Best Scientific Work on COVID-19 and the Fulbright Visiting Researcher award. These accolades reflect his exceptional contributions to environmental engineering and related fields.

Conclusion

Dr. Adel Oulefki’s research has significantly impacted environmental engineering through innovative applications of imaging technologies. His contributions to environmental health, vector control, and infectious disease management, coupled with his collaborative efforts and international recognition, make him a highly deserving candidate for the Research for Environmental Engineering Impact Award.

Publications Top Notes

  1. Dataset of IoT-Based Energy and Environmental Parameters in a Smart Building Infrastructure
    • Authors: Oulefki, A., Amira, A., Kurugollu, F., Soudan, B.
    • Year: 2024
    • Citations: 0
  2. Assessing the Effectiveness of Virtual Reality Serious Games in Post-Stroke Rehabilitation: A Novel Evaluation Method
    • Authors: Masmoudi, M., Zenati, N., Izountar, Y., Oulefki, A., Hamitouche, C.
    • Year: 2024
    • Citations: 0
  3. Detection and Analysis of Deteriorated Areas in Solar PV Modules Using Unsupervised Sensing Algorithms and 3D Augmented Reality
    • Authors: Oulefki, A., Himeur, Y., Trongtirakul, T., Atalla, S., Mansoor, W.
    • Year: 2024
    • Citations: 0
  4. MEMS-Based Microheater with Virtual Reality for Enhanced Thermal Feedback in Medical Applications
    • Authors: Bakha, Y., Merah, S.M., Benbelkacem, S., Atalla, S., Mansoor, W.
    • Year: 2024
    • Citations: 0
  5. Method for Remote Sensing Oil Spill Applications Over Thermal and Polarimetric Imagery
    • Authors: Trongtirakul, T., Agaian, S., Oulefki, A., Panetta, K.
    • Year: 2023
    • Citations: 4
  6. Tumor Lung Visualization and Localization Through Virtual Reality and Thermal Feedback Interface
    • Authors: Benbelkacem, S., Zenati-Henda, N., Zerrouki, N., Bentaleb, A., Liew, A.
    • Year: 2023
    • Citations: 4
  7. Twining Buildings: A Methodological Framework for Design and Implementation Using Home Assistant Technology
    • Authors: Oulefki, A., Amira, A., Kurugollu, F., Alshoweky, M.
    • Year: 2023
    • Citations: 1
  8. Seamless Decision-Making in the Big Data Era: A Modular Approach to Integrating IoT, Cloud Computing, and Data Lakes
    • Authors: Zemmouri, M., Laalam, F.Z., Kazar, O., Mansoor, W., Attala, S.
    • Year: 2023
    • Citations: 0
  9. Cross Data Analysis Platform Based on Big Data Paradigm
    • Authors: Zemmouri, M., Laalam, F.Z., Himeur, Y., Belhadi, A., Mesbahi, N.
    • Year: 2023
    • Citations: 0
  10. Automated Tumor Segmentation in Thermographic Breast Images
    • Authors: Trongtirakul, T., Agaian, S., Oulefki, A.
    • Year: 2023
    • Citations: 2