Luigi Fortuna | Engineering | Academic Excellence Recognition Award

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Prof. Luigi Fortuna | Engineering | Academic Excellence Recognition Award

Free Scientist at University of Catania | Italy

Prof. Luigi Fortuna is a distinguished scholar in Electrical Engineering whose career has been defined by groundbreaking contributions to control theory, nonlinear dynamics, and complex systems engineering. His research has seamlessly integrated theoretical advancements with real-world applications in areas such as plasma control, bio-inspired robotics, and semiconductor innovation. With an exceptional publication record of more than 750 articles, over 13,000 citations, an H-index exceeding 60, and authorship of 24 books, he has established himself as a global leader in his field. He has supervised hundreds of Master’s and Ph.D. students, shaping the future of engineering research worldwide. Recognized internationally, he is an IEEE Life Fellow, IEICE Fellow, and AIAA Fellow, as well as an influential editor, keynote speaker, and project leader in European and global collaborations. His achievements highlight a career dedicated not only to advancing knowledge but also to fostering innovation, mentorship, and international scientific cooperation.

Professional Profiles

Google Scholar | Scopus Profile | ORCID Profile 

Education

Prof. Luigi Fortuna pursued his higher education in Electrical Engineering at the University of Catania, where he graduated with distinction (cum laude). His academic foundation was built upon a strong interest in automation, system theory, and nonlinear dynamics, which would later define his career. Throughout his academic journey, he developed expertise in robust control, complex systems, and bioengineering, blending mathematics, engineering, and physics into multidisciplinary research. He further enhanced his academic profile through visiting researcher roles at leading institutions such as the Joint European Torus (JET) in the United Kingdom, where he contributed to plasma control systems. His education was not limited to technical mastery but also cultivated leadership and vision, preparing him to take on significant roles in academia and international research projects. This strong academic background provided the essential base for his contributions to advanced system theory, innovation in nonlinear circuits, and the development of bio-inspired robotic systems.

Experience

Prof. Luigi Fortuna has a career spanning decades of teaching, research, and leadership in Electrical Engineering and System Theory. He has served as a Full Professor of System Theory at the University of Catania, where he also held leadership roles such as Dean of the Faculty of Engineering and Coordinator of Ph.D. programs. His teaching experience includes delivering more than seventy courses and supervising hundreds of theses, shaping generations of engineers and researchers. Beyond academia, he has played a vital role in advancing international research collaborations through projects supported by the European Union, national funding bodies, and bilateral agreements with global partners. His contributions extend to innovation and technology transfer, having co-invented eleven industrial patents and directed research laboratories in complex systems, microelectronics, and robotics. As a speaker and organizer of major international conferences, he has strengthened global scientific exchange, while his editorial and evaluation board responsibilities demonstrate his influence on research policy.

Research Interest

Prof. Fortuna’s research interests cover a wide spectrum of areas within Electrical Engineering and System Theory, with a strong focus on bridging theoretical innovation with practical applications. His work in robust control and model order reduction has contributed to advancing efficient system design, while his exploration of nonlinear circuits has provided insights into chaos, synchronization, and emerging applications in communications and signal processing. He has also made pioneering contributions to bio-inspired robotics, developing innovative locomotion and control mechanisms inspired by nature. Plasma control for Tokamak devices represents another area where his expertise has significantly influenced energy research and fusion technologies. Furthermore, his interest in complex system engineering and cellular neural networks has expanded the understanding of how large-scale interconnected systems can be modeled and controlled. His interdisciplinary approach continues to drive breakthroughs at the intersection of electronics, control systems, and bioengineering, making his work globally relevant across academia and industry.

Awards and Honors

Prof. Fortuna’s illustrious career has been recognized through numerous awards, fellowships, and honors from prestigious scientific communities. He is an IEEE Life Fellow, reflecting his sustained and impactful contributions to the field of circuits and systems. In addition, he has been honored as a Fellow of both the Institute of Electronics, Information and Communication Engineers (IEICE) and the American Institute of Aeronautics and Astronautics (AIAA), affirming the international breadth of his influence. He has served as Distinguished Lecturer for IEEE, delivered plenary talks at renowned global conferences, and been invited to share his expertise across leading institutions in Asia, Europe, Africa, and the United States. His service as an editor and board member for high-impact journals, as well as chairmanship of major IEEE and IFAC conferences, further highlight his professional standing. These distinctions underscore his dual excellence in advancing research and fostering international collaboration within the global scientific community.

Research Skills

Prof. Fortuna possesses a rich set of research skills that have allowed him to contribute extensively across multiple domains of engineering and applied sciences. He is highly skilled in system modeling, control design, and nonlinear dynamics, with expertise in applying mathematical frameworks to solve complex engineering challenges. His proficiency in advanced computational tools, including MATLAB-based simulations, supports his work in model order reduction, robust control, and bio-inspired system development. He has also demonstrated remarkable innovation in circuit design, chaos theory applications, and bio-robotics, integrating theoretical research with experimental implementations. His ability to lead multidisciplinary teams and manage large-scale international projects reflects strong organizational and leadership skills. Additionally, his patent portfolio illustrates his talent in technology transfer and applied research. With editorial experience and peer-review expertise, he also demonstrates critical evaluation and scientific communication skills, making him a versatile researcher and mentor within academia, industry, and professional societies.

Publication Top Notes

Title: Fractional order systems: modeling and control applications
Authors: R Caponetto, G Dongola, L Fortuna, I Petras
Year: 2010
Citations: 1427

Title: Soft Sensor for Monitoring and Control of Industrial Processes. In Advances in Industrial Control Series (MJ Grimble, MA Johnson, eds.)
Authors: L Fortuna, S Graziani, A Rizzo, MG Xibilia
Year: 2007
Citations: 1187

Title: Chaotic sequences to improve the performance of evolutionary algorithms
Authors: R Caponetto, L Fortuna, S Fazzino, MG Xibilia
Year: 2003
Citations: 663

Title: Timing of surgery following SARS‐CoV‐2 infection: an international prospective cohort study
Authors: GS Collaborative, COVIDSurg Collaborative
Year: 2021
Citations: 616

Title: Soft sensors for product quality monitoring in debutanizer distillation columns
Authors: L Fortuna, S Graziani, MG Xibilia
Year: 2005
Citations: 425

Title: Model order reduction techniques with applications in electrical engineering
Authors: L Fortuna, G Nunnari, A Gallo
Year: 2012
Citations: 331

Title: Effect of COVID-19 pandemic lockdowns on planned cancer surgery for 15 tumour types in 61 countries: an international, prospective, cohort study
Authors: J Glasbey, A Ademuyiwa, A Adisa, E AlAmeer, AP Arnaud, F Ayasra, …
Year: 2021
Citations: 306

Title: A chaotic circuit based on Hewlett-Packard memristor
Authors: A Buscarino, L Fortuna, M Frasca, L Valentina Gambuzza
Year: 2012
Citations: 305

Title: Effects of mobility in a population of prisoner’s dilemma players
Authors: S Meloni, A Buscarino, L Fortuna, M Frasca, J Gómez-Gardeñes, V Latora, …
Year: 2009
Citations: 298

Title: Elective cancer surgery in COVID-19–free surgical pathways during the SARS-CoV-2 pandemic: an international, multicenter, comparative cohort study
Authors: JC Glasbey, D Nepogodiev, JFF Simoes, O Omar, E Li, ML Venn, PGDME, …
Year: 2021
Citations: 292

Title: Chua’s circuit implementations: yesterday, today and tomorrow
Authors: L Fortuna, M Frasca, MG Xibilia
Year: 2009
Citations: 279

Title: Bifurcation and chaos in noninteger order cellular neural networks
Authors: P Arena, R Caponetto, L Fortuna, D Porto
Year: 1998
Citations: 239

Title: Chua’s circuit can be generated by CNN cells
Authors: P Arena, S Baglio, L Fortuna, G Manganaro
Year: 2002
Citations: 225

Conclusion

Prof. Luigi Fortuna is highly deserving of the Academic Excellence Recognition Award. His pioneering work in nonlinear circuits, robust control, and bio-inspired systems has had a lasting impact on both academia and industry. With over four decades of leadership, 758 publications, multiple books, patents, and global collaborations, he exemplifies the very essence of academic excellence. His contributions to training the next generation of scholars, advancing scientific innovation, and strengthening international cooperation make him a model candidate for recognition. Looking ahead, his expertise and leadership will continue to shape the future of engineering, complex systems, and global research networks.

Syamsul Rizal | Engineering | Best Researcher Award

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Dr. Syamsul Rizal | Engineering | Best Researcher Award

Postdoctoral at ICT Convergence Research Center, South Korea

Dr. Syamsul Rizal is an Assistant Professor at Telkom University, Indonesia, and a postdoctoral researcher at Kumoh National Institute of Technology, South Korea, with expertise in machine learning, AI, and blockchain integration. With over five years of teaching experience, he instructs courses in programming and AI, fostering the next generation of tech innovators. His research spans real-time locating systems, biomedical applications of AI, and recently, blockchain with AI, showcasing his focus on emerging, interdisciplinary technology. Dr. Rizal has a strong publication record with contributions to prominent conferences and journals, demonstrating his commitment to advancing AI and machine learning. Honored with a Best Thesis Award and scholarships, he combines technical skill, academic rigor, and practical application in his work. Known for his collaborative spirit and leadership in international research settings, Dr. Rizal is recognized for his contributions to applied AI and his role in innovative technology development.

Professional profile

Education📚

Dr. Syamsul Rizal completed his Master’s and Ph.D. programs in the Department of IT Convergence at the Kumoh National Institute of Technology, South Korea, from 2013 to 2018. His advanced studies focused on integrating emerging technologies across fields such as networked systems, IoT, and AI. As a team leader in the Networked Systems Laboratory, he worked on projects related to ISA100.11a, data virtualization, and image and video processing, gaining hands-on experience in cutting-edge technology. During his doctoral studies, he was honored with a Best Thesis Award in 2015, highlighting his research excellence and innovative approach. His education, supported by a scholarship at Kumoh National Institute of Technology, provided a robust foundation in both theoretical and applied aspects of information technology. Dr. Rizal’s academic journey has equipped him with interdisciplinary expertise, enabling him to address complex challenges in machine learning, blockchain, and AI-driven solutions in his professional career.

Professional Experience🏛️

Dr. Syamsul Rizal has a diverse professional background that spans academic and applied research roles. Currently, he is an Assistant Professor at Telkom University, Indonesia, where he has been teaching since 2019, specializing in programming, artificial intelligence, and mobile application development. His teaching focuses on empowering students with foundational and advanced skills in Python, Java, and C. Alongside teaching, Dr. Rizal is actively involved in research, particularly in machine learning, with projects like AI-driven tea leaf classification. Since 2023, he has also served as a postdoctoral researcher at Kumoh National Institute of Technology in South Korea, where he is developing blockchain systems integrated with AI, reflecting his commitment to emerging technologies. Dr. Rizal’s previous experience includes a postdoctoral role at DGIST, South Korea, where he worked on real-time locating systems and deep learning algorithms for automotive applications. His experience highlights a strong interdisciplinary approach and dedication to innovation.

🔬 Research Interest

Dr. Syamsul Rizal’s research interests are rooted in interdisciplinary applications of advanced technology, particularly in machine learning, AI integration, and networked systems. His work spans diverse areas such as data reconstruction, real-time locating systems (RTLS), and biomedical engineering applications. Dr. Rizal’s research also emphasizes the application of machine learning algorithms for classification tasks, including innovative projects like tea leaf classification and brain stroke detection. He has explored machine learning in biomedical contexts, using techniques like convolutional neural networks (CNNs) for medical image analysis, including retinal pathology and colon cancer classification. Further extending his expertise, Dr. Rizal is engaged in developing blockchain technology with AI capabilities, underscoring his focus on pioneering solutions that leverage AI for security and scalability in decentralized networks. His research reflects a commitment to advancing the practical impact of machine learning and AI across fields as diverse as agriculture, healthcare, and blockchain technology.

🏆Awards and Honors

Dr. Syamsul Rizal has been recognized for his academic excellence and contributions to the field of technology through several awards and honors. Notably, he received the Best Thesis Award in 2015 from the Kumoh National Institute of Technology, South Korea, where he completed both his Master’s and Doctoral studies. This award highlights his exceptional research skills and his innovative contributions during his graduate studies, specifically in networked systems and real-time data communication. Additionally, he was granted a prestigious scholarship to join the Networked System Laboratory at Kumoh, supporting his research in cutting-edge areas such as IoT, virtualization, and image and video processing. These accolades underscore Dr. Rizal’s dedication to advancing technological innovation and his role as a leader in applied research, contributing valuable insights and advancements in fields ranging from machine learning and artificial intelligence to networked systems and data science.

Conclusion

Dr. Syamsul Rizal is a compelling candidate for the Best Researcher Award due to his robust background in machine learning, AI, and systems engineering, combined with a strong publication record and international experience. By further expanding his publication reach and collaborative initiatives, Dr. Rizal could enhance his profile and make an even stronger case for this award, which recognizes impactful and innovative research.

Publications top noted📜

  • ND Miranda, L Novamizanti, S Rizal
    Title: “Convolutional Neural Network pada klasifikasi sidik jari menggunakan RESNET-50”
    Journal: Jurnal Teknik Informatika
    Year: 2020
    Citations: 88
  • YN Fu’adah, I Wijayanto, NKC Pratiwi, FF Taliningsih, S Rizal, …
    Title: “Automated classification of Alzheimer’s disease based on MRI image processing using convolutional neural network (CNN) with AlexNet architecture”
    Journal: Journal of Physics: Conference Series
    Year: 2021
    Citations: 57
  • S Rizal, N Ibrahim, NORKC PRATIWI, S Saidah, RYNUR FUÂ
    Title: “Deep Learning untuk Klasifikasi Diabetic Retinopathy menggunakan Model EfficientNet”
    Journal: ELKOMIKA
    Year: 2020
    Citations: 18
  • S Rizal, T Kartika, GA Septia
    Title: “Studi Etnobotani Tumbuhan Obat di Desa Pagar Ruyung Kecamatan Kota Agung Kabupaten Lahat Sumatera Selatan”
    Journal: Sainmatika
    Year: 2021
    Citations: 17
  • NORKC PRATIWI, NUR IBRAHIM, YNUR FUÂ, S RIZAL
    Title: “Deteksi Parasit Plasmodium pada Citra Mikroskopis Hapusan Darah dengan Metode Deep Learning”
    Journal: ELKOMIKA
    Year: 2021
    Citations: 15
  • AA Pramudita, Y Wahyu, S Rizal, MD Prasetio, AN Jati, R Wulansari, …
    Title: “Soil water content estimation with the presence of vegetation using ultra wideband radar-drone”
    Journal: IEEE Access
    Year: 2022
    Citations: 13
  • AA Santosa, RYN Fu’adah, S Rizal
    Title: “Deteksi Penyakit pada Tanaman Padi Menggunakan Pengolahan Citra Digital dengan Metode Convolutional Neural Network”
    Journal: Journal of Electrical and System Control Engineering
    Year: 2023
    Citations: 10
  • ME Abdulfattah, L Novamizanti, S Rizal
    Title: “Super Resolution pada Citra Udara menggunakan Convolutional Neural Network”
    Journal: ELKOMIKA
    Year: 2021
    Citations: 10
  • I Wijayanto, S Rizal, S Hadiyoso
    Title: “Epileptic electroencephalogram signal classification using wavelet energy and random forest”
    Journal: AIP Conference Proceedings
    Year: 2023
    Citations: 9
  • S Saidah, YN Fuadah, F Alia, N Ibrahim, R Magdalena, S Rizal
    Title: “Facial skin type classification based on microscopic images using convolutional neural network (CNN)”
    Conference: 1st International Conference on Electronics, Biomedical …
    Year: 2021
    Citations: 9
  • YN Fu’adah, S Sa’idah, I Wijayanto, N Ibrahim, S Rizal, R Magdalena
    Title: “Computer Aided Diagnosis for Early Detection of Glaucoma Using Convolutional Neural Network (CNN)”
    Conference: 1st International Conference on Electronics, Biomedical …
    Year: 2021
    Citations: 9
  • HM Lathifah, L Novamizanti, S Rizal
    Title: “Fast and accurate fish classification from underwater video using you only look once”
    Journal: IOP Conference Series: Materials Science and Engineering
    Year: 2020
    Citations: 8

Xu Zhang | Engineering Award | Best Scholar Award

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Dr. Xu Zhang | Engineering Award | Best Scholar Award

Associate professor at Hubei University of Technology, China

Xu Zhang is a distinguished scholar specializing in intelligent non-destructive testing (NDT) technologies. With a solid academic foundation in Acoustics, her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence in NDT systems. Zhang has been the principal investigator on several prestigious projects, including National Natural Science Foundation of China and National Key Research and Development Plan projects. She has made significant contributions to the fields of electromagnetic acoustic transducers (EMATs), guided wave detection methods, and corrosion imaging. Her research is not only innovative but also highly relevant to critical industries such as aerospace, automotive, and infrastructure.

Professional Profile

Education

Xu Zhang’s academic journey began with a Bachelor’s degree in Acoustics from Nanjing University in 2010. She furthered her education with a Master’s and PhD in Acoustics from the prestigious Chinese Academy of Sciences, where she honed her research focus on non-destructive testing technologies. In 2016, she became an Associate Professor in the Department of Mechanical Engineering at Hubei University of Technology. Xu is currently a Visiting Fellow at the University of Bristol, where she collaborates with global experts on advanced NDT methods. Her academic background has equipped her with a deep understanding of the complexities in material testing, structural health monitoring, and the application of electromagnetic and ultrasonic technologies in engineering.

Experience

Xu Zhang has extensive experience in the field of non-destructive testing and advanced materials inspection. Since 2016, she has served as an Associate Professor at Hubei University of Technology, specializing in intelligent NDT technologies. Zhang has been the Principal Investigator (PI) in numerous high-profile national and provincial projects, focusing on ultrasonic and electromagnetic testing techniques for stress corrosion cracking and high-temperature creep materials. Notable projects she has led include the development of an ultrasonic phased array detection system for automotive steering parts and the creation of technology for pipeline corrosion imaging. Her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence into NDT systems. Zhang is also a Senior Member of the Chinese Mechanical Engineering Society and an active participant in global research discussions on intelligent testing methodologies.

Research Focus

Xu Zhang’s research is primarily focused on intelligent non-destructive testing (NDT) technologies, with a specific emphasis on ultrasonic and electromagnetic guided wave techniques. She is dedicated to the development of advanced sensor systems and diagnostic tools that can detect flaws and assess material integrity in complex engineering structures. One of her key areas of research is the integration of artificial intelligence into NDT methodologies, enabling more efficient and accurate defect detection. Zhang’s work has applications in diverse industries, including automotive, aerospace, and infrastructure, particularly in stress corrosion cracking detection, high-temperature material assessment, and pipeline monitoring. Additionally, her research explores the enhancement of testing systems with electromagnetic transducers and phased array technologies, which improve detection sensitivity and system reliability. Her contributions to NDT technology continue to shape the future of materials testing and structural health monitoring.

Awards and Honors

Xu Zhang has been recognized for her pioneering work in non-destructive testing, particularly in the application of electromagnetic and ultrasonic guided wave technologies. As a Principal Investigator (PI), she has secured several prestigious grants and awards, including the National Key Research and Development Plan Project and the National Natural Science Foundation of China Project. Her research on stress corrosion cracking detection, material assessment, and corrosion imaging has earned her numerous accolades. Zhang has also been honored with key research project leadership positions from the Provincial Science and Technology Department, reflecting her influence in advancing the state of engineering diagnostics. She continues to contribute to the scientific community, and her work in non-destructive testing systems is frequently recognized for its practical applications in the fields of materials science and engineering.

Conclusion

Xu Zhang is a leading figure in the field of intelligent non-destructive testing, with an impressive array of research accomplishments and leadership in cutting-edge projects. Her scholarly work in the development of advanced testing systems and her commitment to pushing the boundaries of engineering innovation make her an outstanding candidate for the Best Scholar Award. With a strong foundation in both academic research and practical applications, Zhang’s continued contributions to the field hold the promise of significant advancements in industrial safety and technology.

Publications Top Noted

A novel amplitude enhancement method of EMAT for High-frequency Rayleigh-like waves in Circumferential propagation

Authors: Zhang, X., Li, B., Niu, X., Song, X., Wu, Q.

Citations: 0

Year: 2024

Journal: NDT and E International, 148, 103231

Investigation of an Active Focusing Planar Piezoelectric Ultrasonic Transducer

Authors: Wu, Q., You, B., Zhang, X., Tu, J.

Citations: 0

Year: 2024

Journal: Sensors, 24(13), 4082

Characterization of Small Delamination Defects by Multilayer Flexible EMAT

Authors: Chen, T., Liu, S., Lv, C., Wu, Q., Zhang, X.

Citations: 1

Year: 2024

Journal: IEEE Sensors Journal, 24(12), pp. 19210–19219

Unidirectional focusing Rayleigh waves EMAT for plate surface defect Inspection

Authors: Chen, T., Lou, T., Lv, C., Wu, Q., Zhang, X.

Citations: 0

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Design and experimental study of electromagnetic ultrasonic single-mode guided wave transducer for small-diameter stainless steel tubes

Authors: Tu, J., Zhan, X., Sun, H., Zhang, X., Song, X.

Citations: 3

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Internal and External Pipe Defect Characterization via High-Frequency Lamb Waves Generated by Unidirectional EMAT

Authors: Zhang, X., Li, B., Zhang, X., Yuan, J., Wu, Q.

Citations: 3

Year: 2023

Journal: Sensors (Basel, Switzerland), 23(21)

Bolt Axial Stress Measurement Based on the Dual-Mode Electromagnetic Acoustic Transducer

Authors: Zhang, X., Li, W., Wu, Q., Cai, C., Song, X.

Citations: 2

Year: 2023

Journal: IEEE Sensors Journal, 23(13), pp. 13978–13986

Energy Transfer Efficiency Based Nonlinear Ultrasonic Testing Technique for Debonding Defects of Aluminum Alloy Foam Sandwich Panels

Authors: Tu, J., Yao, N., Ling, Y., Zhang, X., Song, X.

Citations: 0

Year: 2023

Journal: Sensors, 23(6), 3008

Optimized Design of Torsional Guided Wave Magnetostrictive Patch Transducer Based on Reversed Wiedemann Effect

Authors: Li, C., Yang, R., Gu, J., Wang, S., Zhang, X.

Citations: 5

Year: 2023

Journal: Journal of Nondestructive Evaluation, 42(1), 26

Enhancing the Lift-Off Performance of EMATs by Applying an Fe3O4 Coating to a Test Specimen

Authors: Liang, B., Li, Z., Zhai, G., Zhang, X., Dixon, S.

Citations: 5

Year: 2023

Journal: IEEE Transactions on Instrumentation and Measurement, 72, 9502104

 

 

 

Sara El Kourdi | Engineering | Best Scholar Award

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🌟Ms. Sara El Kourdi , Engineering, Best Scholar Award🏆

  •   Sara El Kourdi at Mohammadia Engineering School, Morocco

Sara El Kourdi is a Ph.D. student specializing in waste valorization to bioenergy, biochemicals, and biomaterials at Mohammadia Engineering School, Mohammed V University in Rabat, Morocco. She holds a degree in Process, Energy, and Environmental Engineering from the National School of Applied Sciences, Morocco. Sara’s research focuses on utilizing pyrolysis to convert biomass residues, particularly from the argan tree, into valuable products like bio-oil and biochar. She has contributed significantly to the development of slow pyrolysis simulation models applicable to various biomass types, facilitating optimization for poly-generation. Sara’s professional journey includes experience in technical sales engineering of industrial processes and collaborative research projects between Moroccan and Tunisian universities. Her dedication to research has earned her recognition, including publications in high-impact journals and participation in international conferences.

Author Metrics

Scopus Profile

Google Scholar Profile

Sara El Kourdi is associated with the Ecole Mohammadia d’Ingenieurs, Mohammed V University in Rabat, Morocco. She has been identified in Scopus with the Author Identifier: 57573188100. With 13 citations across 7 documents and an h-index of 3, Sara’s research contributions have made an impact in her field.

Documents

Sara El Kourdi has authored 5 documents indexed in Scopus. These documents encompass her research findings, scholarly articles, and contributions to academic literature. Each document represents a significant aspect of her research journey and expertise in waste valorization and sustainable energy solutions.

h-index

Sara’s h-index of 3 reflects the number of her publications that have received at least 3 citations each. This metric is an indicator of both the productivity and impact of her research output. As her research continues to grow and gain recognition, her h-index may further increase, demonstrating the ongoing influence of her work in the academic community.

Education

Sara El Kourdi graduated from the National School of Applied Sciences, Morocco, in 2018, with a degree in Process, Energy, and Environmental Engineering. Her academic journey equipped her with a strong foundation in engineering principles and a passion for sustainable solutions to environmental challenges.

Research Focus

Sara’s research focuses on waste valorization to bioenergy, biochemicals, and biomaterials, with a specific emphasis on pyrolysis processes. She investigates the potential of converting biomass residues, particularly from the argan tree, into valuable products such as bio-oil, biochar, and gas. Her work involves experimental studies, modeling, and optimization to maximize the energy and chemical yield from various biomass sources.

Professional Journey

Sara El Kourdi embarked on her professional journey after completing her undergraduate studies, gaining experience as a technical sales engineer in the field of industrial processes. However, driven by her passion for research and sustainability, she transitioned into a Ph.D. program at Mohammadia Engineering School, Mohammed V University. Throughout her academic and professional endeavors, Sara has demonstrated a commitment to advancing knowledge in waste valorization and sustainable energy solutions.

Honors & Awards

Sara’s dedication to research and academic excellence has been recognized through various honors and awards. She has received accolades for her contributions to collaborative research projects, publications in prestigious journals, and presentations at international conferences. These honors underscore Sara’s commitment to making significant contributions to her field.

Publications Noted & Contributions

Sara El Kourdi has made substantial contributions to the academic literature in the field of waste valorization and sustainable energy. Her research publications, including papers in high-impact journals and conference proceedings, showcase her expertise in pyrolysis processes and biomass conversion. Sara’s work has contributed valuable insights into the optimization of bioenergy production and the utilization of biomass residues for industrial applications.

Municipal solid waste generation from Morocco and Tunisia, and their possible energetic valorization

  • Authors: S Aboudaoud, S El Kourdi, S Abderafi, MA Abbassi
  • Published in: 2021 9th International Renewable and Sustainable Energy Conference (IRSEC)
  • Pages: 1-6
  • Citations: 6
  • Year: 2021

Pyrolysis Technology Choice to Produce Bio-oil, from Municipal Solid Waste, Using Multi-criteria Decision-making Methods

  • Authors: S El Kourdi, S Aboudaoud, S Abderafi, A Cheddadi, AM Ammar
  • Published in: Waste and Biomass Valorization
  • Pages: 1-18
  • Citations: 5
  • Year: 2023

Potential Assessment of Combustible Municipal Wastes in Morocco and their Ability to Produce Bio-Oil by Pyrolysis

  • Authors: S El Kourdi, S Aboudaoud, S Abderafi, A Cheddadi
  • Published in: Materials Science Forum 1073
  • Pages: 149-154
  • Citations: 4
  • Year: 2022

Valorizing argan residues into biofuels and chemicals through slow pyrolysis

  • Authors: S El kourdi, A Chaabane, S Abderafi, AA Mohamed
  • Published in: Results in Engineering
  • Article Number: 101659
  • Citations: 1
  • Year: 2023

Argan Cake Oil Transesterification Kinetics and an Optimized Choice of a High-Performance Catalyst for Biodiesel Production

  • Authors: N Bahani, S El Kourdi, S Abderafi
  • Published in: Waste and Biomass Valorization
  • Pages: 1-20
  • Citations: 1
  • Year: 2023

Simulation and multi-objective optimization of argan residues slow pyrolysis for polygeneration of bio-oil, biochar, and gas products

  • Authors: Sara El Kourdi, Souad Abderafi, Abdelkhalek Cheddadi, Jemaa Mabrouki …
  • Published in: Energy Conversion and Management
  • Volume: 304
  • Year: 2024

These publications demonstrate Sara’s expertise in waste valorization, particularly through pyrolysis processes, and her contributions to sustainable energy research.

Research Timeline

Sara El Kourdi’s research journey has been characterized by a systematic and progressive exploration of waste valorization and biomass conversion processes. From her initial experiments on argan residues to the development of sophisticated pyrolysis simulation models, Sara’s research timeline reflects a trajectory of continuous learning, innovation, and collaboration. Her contributions have advanced understanding in the field and paved the way for future developments in sustainable energy and environmental engineering.