Wenbo Zhou | AI security | Best Researcher Award

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Assoc. Prof. Dr. Wenbo Zhou | AI security | Best Researcher Award

Wenbo Zhou is an Associate Professor at the University of Science and Technology of China, specializing in AI security, particularly in the areas of Deepfake generation and detection. He holds a B.S. from Nanjing University of Aeronautics and Astronautics (2014) and a Ph.D. from the University of Science and Technology of China (2019). He is an IEEE member and an influential researcher in AI security. Zhou has won multiple prestigious awards, including the “Distinguished Artifact Award” at ACM CCS. He was part of the team that won second place in the world in the Deepfake Detection Challenge (DFDC), earning a prize of 300,000 US dollars. His development of DeepFaceLab, a globally recognized Deepfake tool, has cemented his place as a leader in the field of AI security. Zhou has also published widely in high-impact journals and conferences, contributing significantly to advancements in AI and cybersecurity.

Profile

Education

Wenbo Zhou received his B.S. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2014. Following his undergraduate studies, he pursued his Ph.D. at the University of Science and Technology of China, Hefei, China, and completed his doctoral degree in 2019. His research during his Ph.D. focused on AI security, laying the foundation for his future work in Deepfake detection and adversarial machine learning. Zhou’s academic journey has been marked by a blend of rigorous coursework and groundbreaking research. His Ph.D. work, combined with hands-on experience in AI security tools like DeepFaceLab, set him apart as a leader in the field. Throughout his education, Zhou demonstrated a commitment to advancing technology for practical applications, as evidenced by his multiple patents and innovations in AI security.

Experience

Wenbo Zhou is currently an Associate Professor at the University of Science and Technology of China (USTC). He has led over 10 research projects funded by the Natural Science Foundation of China, with a total funding exceeding ¥20 million. His extensive experience in AI security includes significant contributions to the detection and generation of Deepfakes, with his tools like DeepFaceLab gaining global recognition. Zhou has also been a visiting scholar at Microsoft Research, where he further refined his research on AI and cybersecurity. His work on various patents, such as those in Deepfake detection, shows his ability to bridge theoretical research with practical solutions. Zhou’s expertise extends to peer-reviewed publications in top-tier journals like IEEE Transactions on Information Forensics & Security and Pattern Recognition. His multidisciplinary approach and collaborations with both academia and industry have placed him at the forefront of AI security research.

Research Focus

Wenbo Zhou’s research focuses on AI security, with particular expertise in Deepfake generation and detection, adversarial examples, and steganography. His work addresses critical issues in digital forensics, such as the authentication of media and the detection of manipulated content. Zhou has made significant strides in Deepfake detection, contributing to the global conversation about digital disinformation and cybersecurity. His development of DeepFaceLab, one of the most influential Deepfake tools worldwide, has revolutionized the field of face-swapping and manipulation detection. In addition to Deepfakes, Zhou explores adversarial machine learning, aiming to defend AI systems against vulnerabilities exploited by malicious actors. His research also touches on areas like watermarking and the development of robust image processing techniques to combat the misuse of AI in creating counterfeit media. Zhou’s work not only advances theoretical AI security but also provides practical solutions for combating emerging threats in the digital world.

Publication Top Notes

  • Multi-attentional deepfake detection 🧠
  • Spatial-phase shallow learning: Rethinking face forgery detection in frequency domain 📡
  • Dup-net: Denoiser and upsampler network for 3D adversarial point clouds defense 🖼️
  • Model watermarking for image processing networks 💧
  • Hairclip: Design your hair by text and reference image 💇‍♂️
  • Finfer: Frame inference-based deepfake detection for high-visual-quality videos 🎥
  • A new rule for cost reassignment in adaptive steganography 💻
  • {X-Adv}: Physical adversarial object attacks against X-ray prohibited item detection 📦
  • Initiative defense against facial manipulation 🧑‍⚖️

 

 

Mudassar Razzaq | numerical simulation | Best Researcher Award

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Dr. Mudassar Razzaq | numerical simulation | Best Researcher Award

Research Associate, University of applied sciences Bochum, Germany.

Dr. Mudassar Razzaq is an experienced academic and researcher with over two decades of expertise in STEM education, specializing in applied mathematics, computational modeling, and fluid-structure interaction (FSI). He has worked extensively in both industry and academia, holding various leadership roles. His research integrates high-performance computing with simulation, focused on mathematical modeling of coupled problems. Dr. Razzaq has supervised numerous graduate and Ph.D. students and contributed to several international conferences. Currently, he is a Visiting Professor at the International School of Management, Germany, and a Research Lead at Bochum University of Applied Sciences, specializing in multiphase flow simulations.

Profile:

Google Scholar 

Education 🎓

Dr. Mudassar Razzaq holds a Ph.D. in Applied Mathematics (Computational and Applied Mathematics) from the Technical University of Dortmund, Germany, where his dissertation focused on fluid-structure interaction using finite element methods. He completed his M.Phil. in Applied Mathematics from Quaid-i-Azam University, Islamabad, Pakistan, specializing in fluid dynamics. He also earned an M.Sc. in Mathematics from Quaid-i-Azam University, with a focus on applied mathematics and statistics. His academic journey began with a B.Sc. in Mathematics and Physics from the University of Punjab, Lahore, Pakistan.

Professional Experience 💼

Dr. Razzaq’s career spans academic and industry roles. He is currently a Visiting Professor in Management Information Systems at the International School of Management, Germany. Previously, he served as an Assistant Professor at the Lahore University of Management Sciences (LUMS), Pakistan, where he taught various mathematics and engineering courses. His industry experience includes working as a Senior CFD Engineer at IANUS Simulation GmbH in Germany. He has also contributed to research at the Weierstrass Institute for Applied Analysis and Stochastic in Berlin and various other institutions in Germany.

Awards & Honors 🏆

Dr. Mudassar Razzaq has received several prestigious awards and fellowships throughout his career, including a faculty travel grant for the International Multigrid Conference in China (2019) and a faculty start-up research grant in 2017. He was awarded the HEC-DAAD scholarship for his Ph.D. studies, receiving significant funding for his research. He also co-led the ExtremSimOpt research project funded by the Federal Ministry of Education and Research (BMBF), Germany, in 2020. In 2021, he won the first prize for a poster presentation.

Research Focus 🔬

Dr. Razzaq’s research primarily revolves around computational and applied mathematics, with a focus on fluid-structure interaction (FSI), high-performance computing, and multiphysics simulations. His work includes the development of finite element simulation techniques and numerical solvers for FSI and CFD applications in bioengineering and optimization. He is particularly interested in modeling multiphase flows, thermodynamics, and the application of statistical and machine learning models in various scientific fields such as finance and engineering. His research is highly interdisciplinary, bridging mathematics, engineering, and data science.

Publications 📚

  1. Numerical benchmarking of fluid-structure interaction: A comparison of different discretization and solution approaches
  2. Numerical simulation and benchmarking of a monolithic multigrid solver for fluid-structure interaction problems with application to hemodynamics
  3. Finite element analysis of bi-viscosity fluid enclosed in a triangular cavity under thermal and magnetic effects
  4. FEM multigrid techniques for fluid–structure interaction with application to hemodynamics
  5. Finite element simulations for energy transfer in a lid-driven porous square container filled with micropolar fluid: Impact of thermal boundary conditions and Peclet number
  6. Numerical simulation and benchmarking of fluid-structure interaction with application to hemodynamics
  7. Computational approach on three-dimensional flow of couple-stress fluid with convective boundary conditions
  8. Finite element simulation techniques for incompressible fluid structure interaction with applications to bioengineering and optimization
  9. The impact of variable fluid properties on hydromagnetic boundary layer and heat transfer flows over an exponentially stretching sheet
  10. Simulation of intra‐aneurysmal blood flow by different numerical methods
  11. Numerical benchmarking of fluid-structure interaction between elastic object and laminar incompressible flow
  12. Numerical simulation of laminar incompressible fluid-structure interaction for elastic material with point constraints
  13. Analysis of biomagnetic blood flow in a stenosed bifurcation artery amidst elastic walls
  14. Numerical techniques for solving fluid-structure interaction problems with applications to bio-engineering
  15. A simplified finite difference method (SFDM) solution via tridiagonal matrix algorithm for MHD radiating nanofluid flow over a slippery sheet submerged in a permeable medium
  16. Multi-objective optimization of a fluid structure interaction benchmarking

Yen-Liang Chen | deep learning | Best Researcher Award

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Prof. Dr. Yen-Liang Chen | deep learning | Best Researcher Award

Chair Professor, National Central University, Taiwan

Professor Yan-Liang Chen is a distinguished Chair Professor in the Department of Information Management at National Central University, Taiwan. He holds a Ph.D. in Information Science from National Tsing Hua University. With over four decades of academic experience, Professor Chen has led several significant projects, advancing the understanding of e-commerce systems, data analytics, and machine learning. His interdisciplinary research focuses on integrating business systems with information technology to drive digital transformation. In addition to his academic responsibilities, he has served as an advisor to the Ministry of Science and Technology and as Editor-in-Chief for renowned journals like the Journal of Electronic Commerce Research. Professor Chen has been recognized globally for his impactful work, making substantial contributions to the field of data analysis, decision support systems, and business intelligence.

Profile:

Scopus

Education:

Professor Yan-Liang Chen earned his Ph.D. in Information Science from National Tsing Hua University, one of Taiwan’s top academic institutions. His educational foundation in Information Science provided the perfect platform for his future research endeavors in e-commerce systems, data analysis, and machine learning. The focus of his doctoral research laid the groundwork for his long-standing contributions to various critical areas such as decision support systems, business intelligence, and sentiment analysis. His academic journey has continuously pushed the boundaries of knowledge, driving advancements in both the theoretical and practical aspects of information management. This foundation, alongside years of extensive teaching and research, has established Professor Chen as a leader in his field, shaping the next generation of scholars and professionals in e-commerce and data analytics.

Experience:

Professor Yan-Liang Chen has a rich academic career that spans over 40 years at National Central University in Taiwan. He began his tenure in 1978 as an Associate Professor, eventually rising to the position of Chair Professor in the Department of Information Management. From 2004 to 2007, he served as the Director of the Department of Information Management and was also the Director of the University Library from 2009 to 2011. Throughout his career, Professor Chen has led numerous research projects and has significantly contributed to the development of Taiwan’s academic and technological landscape. He has also held key advisory roles in various government bodies, such as the Ministry of Science and Technology and National Science Council, helping shape policies on information technology and e-commerce. His extensive leadership roles have made him a prominent figure in both academic and professional spheres.

Awards and Honors:

Professor Yan-Liang Chen has received numerous prestigious awards throughout his career. Notably, he has been honored with the Ministry of Science and Technology Distinguished Research Award in both 2003 and 2009, recognizing his groundbreaking contributions to e-commerce and information technology. In 2015, he was awarded the National Science Council Academic Award for his sustained excellence in research. From 2018 to 2024, he was named a Merit MOST Research Fellow, and in 2024, he received the esteemed MOST Distinguished Special Research Fellow honor. His exceptional research output has earned him a spot in the Global Top 2% Scientist Lifetime and Annual Rankings (2020-2024). Professor Chen’s remarkable academic career and continued impact have been recognized globally, solidifying his reputation as one of the leading scientists in his field.

Research Focus:

Professor Yan-Liang Chen’s research focuses primarily on E-commerce Systems and the integration of information technology with business systems. His areas of expertise include data analysis, machine learning, business intelligence, decision support systems, and sentiment analysis. He is particularly interested in understanding and optimizing the dynamics of e-commerce logistics, consumer behavior, and personalized marketing strategies. His work on basket analysis, cross-selling, and customer purchase sequence analysis has significantly advanced the understanding of consumer purchasing patterns, which are crucial for targeted marketing and enhancing customer retention. Additionally, Professor Chen has worked on text mining and social network analysis, applying these techniques to improve recommendation systems and predictive analytics in the digital commerce environment. His interdisciplinary approach has allowed him to bridge the gap between information technology and practical business applications, leading to innovations in digital transformation.

Publications:

  1. A Novel Ensemble Model for Link Prediction in Social Network 🤖📱
  2. G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction ⏳💡
  3. Using Personalized Next Session to Improve Session-Based Recommender Systems 🔄📊
  4. A Deep Recommendation Model Considering the Impact of Time and Individual Diversity ⏰🔍
  5. A Novel Virtual-Communicated Evolution Learning Recommendation 💻🧠
  6. A Deep Multi-Embedding Model for Mobile Application Recommendation 📱🔗
  7. New Information Search Model for Online Reviews with the Perspective of User Requirements 🌐🔍
  8. A Cross-Platform Recommendation System from Facebook to Instagram 📘📸
  9. Aspect-Based Sentiment Analysis with Component Focusing Multi-Head Co-Attention Networks 🧠💬
  10. An Ensemble Model for Link Prediction Based on Graph Embedding 🔗📉

Prof. Dr. Elisa Bicalho | Seed Physiology | Women Researcher Award

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Prof. Dr. Elisa Bicalho | Seed Physiology | Women Researcher Award

Professor of Higher Education, Federal University of Viçosa – Florestal Campus, Brazil

Elisa Monteze Bicalho is a renowned researcher and educator in seed physiology and plant biology. She holds a PhD in Plant Biology from the Federal University of Minas Gerais (UFMG) and is currently a professor in the Postgraduate Program in Plant Physiology at the University of Lavras (UFLA). With a deep focus on seed germination, dormancy, and the impact of abiotic stress on seeds and seedlings, she has significantly contributed to the scientific understanding of these areas. Dr. Bicalho is also an associate editor for the European Journal of Horticultural Science and a member of the International Seed Testing Association (ISTA) Storage Committee. Her work has been published widely in prominent scientific journals, reflecting her leadership in seed science.

Profile

Orcid

Education

Dr. Elisa Monteze Bicalho completed her PhD in Plant Biology at UFMG, with a research focus on seed physiology. She also undertook a collaborative research period at the University of Barcelona. Her master’s degree in Phytotechnics/Plant Production was earned at the Federal University of Viçosa (UFV), where she focused on seed germination and reserve mobilization. Dr. Bicalho’s academic journey began with a Bachelor’s degree in Biological Sciences from UFV. She also expanded her expertise with several postdoctoral positions, further enhancing her research in seed physiology. Throughout her education, she has been awarded scholarships from CAPES and CNPq, ensuring her contributions to the field of seed biology are well-supported and recognized globally.

Experience

Dr. Elisa Monteze Bicalho has a rich academic and research experience. She is currently a professor at UFLA’s Postgraduate Program in Plant Physiology. Her academic roles include lecturing undergraduate and postgraduate students in plant physiology and seed biology. She has contributed to various research projects focused on seed dormancy, stress tolerance, and the environmental conditions affecting seed germination. Additionally, she has collaborated with national and international research institutions, such as the University of Barcelona and the International Seed Testing Association (ISTA). Dr. Bicalho’s involvement in seed physiology extends beyond teaching and research to leadership roles in several scientific committees. Her collaborative research projects often focus on advancing methods like priming for improving seed viability, especially in challenging environmental conditions. She has also guided numerous graduate students in their seed physiology research.

Awards and Honors

Dr. Elisa Monteze Bicalho has earned numerous awards and recognitions for her contributions to plant science. In 2021, she was recognized for the best thesis in her department for her research on the bio-herbicidal potential of Vanillosmopsis arborea. Her work on the rehabilitation of degraded areas using native plant species has earned recognition in environmental science circles. Dr. Bicalho’s expertise in seed physiology and plant stress tolerance has also garnered her recognition in various scientific communities. Furthermore, her contributions to plant research were acknowledged through prestigious scholarships from CNPq and CAPES during her doctoral and postdoctoral training. Her active participation in shaping the field of seed physiology is further underlined by her role as an associate editor for the European Journal of Horticultural Science and member of the ISTA Storage Committee.

Research Focus

Dr. Elisa Monteze Bicalho’s research focuses on seed physiology, particularly the study of seed germination, dormancy, and the impact of abiotic stress on seeds and seedlings. Her work explores methods to improve seed quality and seedling establishment in challenging environments. Dr. Bicalho’s research addresses seed priming techniques to overcome the limitations of seed storage and germination, especially in semi-arid regions. She is also deeply involved in research on how environmental stress factors, such as salinity and temperature, affect seed performance. Additionally, her work contributes to the restoration of degraded ecosystems through the use of native species and the study of seed physiology under stress. With a strong commitment to both fundamental and applied research, Dr. Bicalho aims to enhance plant regeneration and improve agricultural practices, ensuring sustainable solutions for plant production and conservation.

Publication Top Notes

  • Halopriming as a tool for maintaining the vigor of sunflower seeds post-storage 🌱🌞
  • Drought tolerance: a perspective about leaf venation and the role of auxin 🌾💧
  • Assessing the feasibility of using Acrocomia aculeata (Arecaceae) for the rehabilitation of iron ore tailings 🌿⛏️
  • COLORED LED REDUCES ENERGY USE, AFFECTING LETTUCE SEED GERMINATION, GROWTH, AND ANTIOXIDANT ACTIVITY POSITIVELY 💡🥬
  • Be prepared: how does discontinuous hydration in Tabebuia heterophylla seeds induce stress tolerance in seedlings? 🌳💦
  • Strategies induced by methyl jasmonate in soybean seedlings under water restriction and mechanical wounding 🌱💪
  • New Perspective on the Use of α-Bisabolol for Weed Control 🌿⚖️
  • Soil seed banks, persistence and recruitment: memories of a partially non-lived life? 🌍🌾
  • Photochemical attributes determine the responses of plant species from different functional groups of ferruginous outcrops when grown in iron mining substrates 🪨🌱
  • Differential composition of reserves and oil of Moringa oleifera seeds cultivated in states of Northeast Brazil 🌿

 

Li-Chun Chang | Gastroenterology | Best Researcher Award

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Dr. Li-Chun Chang | Gastroenterology | Best Researcher Award

Associate professor, National Taiwan University Hospital, Taiwan 

Dr. Li-Chun Chang is an esteemed attending physician and clinical associate professor in the Department of Internal Medicine at National Taiwan University Hospital. Specializing in gastroenterology, he is a recognized leader in digestive endoscopy. Dr. Chang is actively involved in numerous academic and clinical societies, currently serving as the Deputy Secretary-General for The Digestive Endoscopy Society of Taiwan. With extensive training in internal medicine and gastroenterology, he has dedicated his career to advancing the field through both teaching and research. His clinical expertise extends to endoscopic techniques and gastrointestinal diseases, and his commitment to improving patient care is evident through his leadership and contributions to medical research. Dr. Chang’s focus on innovation and medical excellence has garnered him both national and international recognition.

Profile

Education 

Dr. Li-Chun Chang’s educational journey began at Chung-San Medical University, where he earned his degree in Medicine from the Department of Medicine (1995-2002). He then pursued advanced studies at National Taiwan University (NTU), completing a Master of Science in Clinical Medicine in 2012 and a Ph.D. in Clinical Medicine in 2019. His academic achievements reflect his commitment to understanding and improving clinical medicine, particularly in the field of gastroenterology. His research during his postgraduate education at NTU laid the foundation for his later professional accomplishments, combining both theoretical knowledge and hands-on clinical expertise. Dr. Chang’s educational path is marked by his drive for excellence, making him a well-respected academician and clinical educator, playing an instrumental role in shaping the next generation of medical professionals.

Experience 

Dr. Li-Chun Chang’s professional career spans multiple prestigious positions, showcasing his expertise in internal medicine and gastroenterology. He began his career as a resident in the Department of Internal Medicine at National Taiwan University Hospital from 2004 to 2008. Following this, he served as the Chief Resident and Fellow in the Division of Gastroenterology from 2008 to 2009. Dr. Chang continued to climb the academic and clinical ladder, becoming an attending physician at NTU Hospital’s Jin-Shan and Bei-Hu branches. In addition to his clinical work, he has held teaching roles, including Clinical Lecturer (2014-2018) and Clinical Assistant Professor (2018-2024). His leadership extends beyond the hospital, with roles such as Deputy Secretary-General of the Digestive Endoscopy Society of Taiwan (2019-present). He also served as a research fellow at Tokyo Medical University in 2024. Dr. Chang’s extensive experience has made him a key figure in the field of gastroenterology.

Awards and Honors 

Dr. Li-Chun Chang has earned numerous awards and honors throughout his distinguished career, underscoring his contributions to the medical field. In 2014, he received the Outstanding Article Award from Professor Juei-Low Sung’s Research Foundation. His outstanding academic and research work also earned him the Asian Young Endoscopist Award in 2016. That same year, his excellent poster presentation at the International Digestive Endoscopy Network earned him further recognition. He was selected for the Rising Star Program at the 1st Joint Session between JDDW&KDDW&TDDW in 2017. These accolades highlight Dr. Chang’s commitment to advancing the field of gastroenterology and digestive endoscopy. His ongoing excellence in research and education continues to bring attention and praise to his work on both a national and international level, showcasing his unwavering dedication to the field and to improving patient care globally.

Research Focus

Dr. Li-Chun Chang’s research focuses primarily on gastroenterology, with an emphasis on endoscopic procedures and gastrointestinal diseases. His work explores innovative diagnostic and therapeutic techniques in the realm of digestive endoscopy, particularly in the early detection of colorectal cancer and adenomas. Dr. Chang is deeply involved in studies investigating the effectiveness of various endoscopic approaches, including cold versus hot snare polypectomy and the use of machine learning in screening for early-stage colorectal neoplasms. He has also contributed to research on biomarkers such as circulating nucleosomes and extracellular vesicles for detecting advanced adenomas and colorectal cancer. Dr. Chang’s research interests extend to exploring the molecular and cellular mechanisms underlying colorectal cancer progression, with a focus on inflammation and immune responses. His work aims to improve clinical practices in gastroenterology and ultimately enhance patient outcomes.

Publication Top Notes

  1. “Effect of a novel artificial intelligence–based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting” 📑🤖
  2. “Impact of Time Period and Birth Cohort on the Trend of Advanced Neoplasm Prevalence in the 40–49 Average-Risk Screening Population” 🕰️👨‍⚕️
  3. “Bleeding Risk of Cold Versus Hot Snare Polypectomy for Pedunculated Colorectal Polyps Measuring 10 mm or Less: Subgroup Analysis of a Large Randomized Controlled Trial” ⚖️🔬
  4. “Improving the Purity of Extracellular Vesicles by Removal of Lipoproteins from Size Exclusion Chromatography- and Ultracentrifugation-Processed Samples Using Glycosaminoglycan-Functionalized Magnetic Beads” 🧬🔬
  5. “Oral microbiome and serological analyses on association of Alzheimer’s disease and periodontitis” 🦠🧠

 

 

Noureddine Chaachouay | Phytotherapy | Best Researcher Award

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Assist. Prof. Dr. Noureddine Chaachouay | Phytotherapy | Best Researcher Award

Professor, Hassan First University, Settat, Morocco

Prof. Dr. Necibe Fusun Oyman Serteller is a distinguished academic in Electrical-Electronic Engineering at Marmara University, with over two decades of teaching experience. She earned her bachelor’s degree in 1989 from Istanbul Technical University (ITU), followed by postgraduate studies at ITU and a doctorate from Marmara University in 2000. Her research interests include electric machine modeling, numerical analysis of electrical systems, electromagnetic field theory, and engineering education. Prof. Dr. Serteller is passionate about guiding the next generation of engineers, advising PhD and Master’s students, and contributing to advancements in electrical engineering. She has authored multiple books, published over 15 research papers in reputable journals, and is actively involved in both academia and industry. With numerous national collaborations and an international partnership, she is recognized for her practical innovations and contributions to the field of electrical engineering.

Profile

Orcid

Education

Prof. Dr. Necibe Fusun Oyman Serteller completed her undergraduate education at Istanbul Technical University (ITU), Faculty of Electrical-Electronic Engineering, graduating in 1989. She pursued her postgraduate studies at ITU and completed them in 1996. Subsequently, Prof. Dr. Serteller earned her doctorate from Marmara University’s Faculty of Technology, Department of Electrical-Electronic Engineering, in 2000. Throughout her academic journey, she focused on the core subjects of electric machine modeling, design, and the numerical analysis of electrical systems. Her doctoral research laid the foundation for her extensive contributions to the electrical engineering field. With a passion for education, she has continuously updated her knowledge base to reflect the evolving needs of the industry and academia. Prof. Dr. Serteller’s strong academic background has played a critical role in shaping her research focus and guiding her as a mentor to future engineers and researchers.

Experience

Prof. Dr. Necibe Fusun Oyman Serteller has over 20 years of experience as a lecturer in the Department of Electrical-Electronics at Marmara University. Since joining in 2000, she has been dedicated to advancing research and education in electrical engineering. Her experience spans both theoretical and practical aspects of electric machine modeling, numerical analysis, and electromagnetic field theory. She has guided countless PhD and Master’s students, helping them navigate their research projects while fostering a robust academic environment. In addition to her academic achievements, Prof. Dr. Serteller has collaborated on various industry consultancy projects, offering her expertise in solving real-world engineering challenges. She has published over 15 research papers and authored multiple books on electric machine modeling and design. As an active editorial board member and a prominent figure in IEEE societies, Prof. Dr. Serteller continues to contribute to the advancement of electrical engineering worldwide.

Research Focus

Prof. Dr. Necibe Fusun Oyman Serteller’s primary research focus revolves around the modeling, analysis, and design of electric machines, particularly through numerical methods. Her work explores the electromagnetic field theory and its application in the modeling and design of various electrical systems. She is particularly interested in the numerical solutions of electromagnetic fields, which play a crucial role in enhancing the performance and efficiency of electric machines. Prof. Dr. Serteller’s research integrates theoretical knowledge with simulation techniques, enabling the design of innovative solutions for modern electrical systems. Additionally, her research efforts extend to the development of advanced educational techniques for teaching engineering students, ensuring they gain practical insights alongside theoretical learning. Her ongoing and completed research projects have made significant contributions to both academia and industry, focusing on the practical applications of electrical engineering principles to solve real-world challenges.

Publication Top Notes

  1. Electric Machine Design and Modeling: Theoretical Approaches and Applications 📚
  2. Electromagnetic Field Theory and Numerical Solutions for Electrical Systems 🔬
  3. Modeling of Electrical Systems for Industrial Applications 🏭
  4. Electric Machines: Numerical Approaches and Simulations ⚙️
  5. Numerical Analysis of Electromagnetic Fields in Electric Machines 📏
  6. Advances in Electric Machine Design and Performance Optimization ⚡
  7. Engineering Education: New Approaches and Methodologies 🎓
  8. Electric Machines in Modern Electrical Systems 🔌
  9. Practical Approaches to Electric Machine Modeling and Analysis 💡
  10. Innovative Solutions in Electrical Engineering: Modeling and Design 🌟

 

Samuel Polo | Sustainable Manufacturing | Best Researcher Award

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Mr. Samuel Polo | Sustainable Manufacturing | Best Researcher Award

Student, National University of Distance Education (UNED), Spain

👨‍🔬 Samuel Polo Alonso is a dedicated mechanical engineer specializing in mechanical and industrial manufacturing design. With over three years of experience in the machine tool sector, Samuel has excelled in developing parts and assemblies for complex machines. He is passionate about 3D modeling and continuously works to stay updated with the latest technological advancements. Samuel’s expertise extends to project management, having successfully managed and collaborated on teams for large-scale milling machine projects and injection mold production. His professional journey is complemented by academic contributions, including published articles in journals and presentations at conferences. Samuel’s combination of practical skills and research-driven expertise positions him as a promising leader in mechanical engineering. 🌍📚

Profile

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Education

🎓 Samuel holds a Master’s Degree in Advanced Manufacturing Engineering from the National University of Distance Education (UNED), equipping him with a deep understanding of the latest manufacturing technologies. He also earned a Bachelor’s Degree in Mechanical Engineering from the University of Burgos (UBU), where he laid the foundation for his engineering knowledge. His education blends theoretical and practical knowledge, allowing him to contribute to both industrial practices and academic advancements. Samuel’s studies have provided him with a comprehensive background in mechanical systems, materials, and design methodologies, which he applies in his work and research endeavors. This combination of high-level education and hands-on experience makes him a strong asset in the engineering and manufacturing sectors. 💡📘

Experience

💼 Samuel has gained valuable experience through his roles at notable companies such as Hypatia GNC Accesorios, Nicolás Correa, and Grupo Antolín. At Hypatia, he was responsible for the design and development of large milling machines, demonstrating his ability to handle complex projects. His role also included managing project teams, ensuring deadlines and quality standards were met. At Nicolás Correa, Samuel developed mechanical solutions for large milling machines, further enhancing his problem-solving and engineering expertise. Additionally, he supervised machining projects at Grupo Antolín, focusing on the production of injection molds, where he utilized his skills in project management and design to ensure efficient manufacturing processes. Samuel’s experience in these key areas has honed his technical abilities and leadership skills, positioning him as a well-rounded engineer with a deep understanding of both design and manufacturing. 🛠️🤝

Research Focus

🔬 Samuel’s research primarily focuses on the evolution and current trends in cooling and lubrication techniques for sustainable machining. His work aims to optimize these processes to improve efficiency and reduce environmental impact in the manufacturing industry. By exploring the relationship between cooling, lubrication, and sustainability, Samuel contributes to the development of more eco-friendly and efficient machining methods. His systematic review of these techniques, in collaboration with other researchers, sheds light on the latest advancements in the field. Samuel’s research efforts are grounded in a practical understanding of mechanical systems, and his findings provide valuable insights for improving machining processes in industrial settings. With his background in mechanical design and project management, Samuel continues to pursue research that bridges the gap between theory and real-world applications, pushing for advancements in both the research and industrial spheres. 🌱🔧

Publication Top Notes

📄 Evolution and Latest Trends in Cooling and Lubrication Techniques for Sustainable Machining: A Systematic Review (2025)
DOI: 10.3390/pr13020422

Ali Mubaraki | Applied Mathematics | Best Researcher Award

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Dr. Ali Mubaraki | Applied Mathematics | Best Researcher Award

Professor assistant, Taif University, Saudi Arabia.

Dr. Ali Mohammed Ali Mubaraki is an accomplished academic and researcher in the field of mathematics, currently serving as an Assistant Professor at Taif University, Saudi Arabia. He completed his Ph.D. in Mathematics from Keele University, UK, in 2021, specializing in asymptotic models for surface waves in coated elastic solids. With a rich academic background, including a Master’s from Taibah University and a Bachelor’s from King Abdulaziz University, Dr. Mubaraki’s work focuses on wave propagation, elasticity, and surface waves. He has contributed significantly to multiple publications and remains active in advanced research areas. He is an influential member of the academic community, having worked as a lecturer at the Federal University of Dutse, Nigeria, prior to his tenure at Taif University. His expertise extends to areas such as MATHEMATICA, Maple, and LaTeX, making him a valued asset in both teaching and research.

Education

Dr. Mubaraki holds a Doctor of Philosophy (Ph.D.) in Mathematics from Keele University (2021), where his thesis focused on surface wave propagation in coated elastic solids under varying conditions. Before that, he earned a Master of Science (M.Sc.) from Taibah University, Saudi Arabia (2016), where he studied nearly open sets in topological spaces, achieving a CGPA of 4.87 out of 5.0. His academic journey began with a Bachelor of Science (B.Sc.) in Mathematics from King Abdulaziz University, Saudi Arabia (2001), graduating with a CGPA of 4.27 out of 5.0. Dr. Mubaraki’s educational trajectory has been marked by excellence, supported by scholarships throughout his studies, including full-time doctorate and master’s scholarships from Taif University and the Saudi Ministry of Education.

Experience

Dr. Mubaraki’s professional experience includes his current position as Assistant Professor in the Department of Mathematics at Taif University since 2021. Prior to this, he served as a Lecturer I at the Federal University of Dutse, Nigeria, for nearly seven years (2014-2021). Additionally, Dr. Mubaraki has extensive teaching experience as a Classroom Teacher in Jizan and Madinah, Saudi Arabia, from 2001 to 2014. His teaching expertise spans a range of mathematical fields, including wave theory, elasticity, and differential equations. At Taif University, he engages in both undergraduate and graduate-level teaching while conducting cutting-edge research in mathematical modeling, wave propagation, and elasticity. He utilizes software like MATHEMATICA, Maple, and LaTeX to complement his teaching and research endeavors.

Awards and Honors

Dr. Ali Mubaraki has earned notable scholarships in recognition of his academic excellence. He was awarded a full-time Doctorate Degree Scholarship from Taif University (2015-2021), as well as a full-time Master’s Degree Scholarship from the Saudi Ministry of Education to study at Taibah University (2009-2011). These scholarships are a testament to his exceptional academic performance and research potential. Throughout his career, Dr. Mubaraki’s research contributions have gained recognition from international academic communities, further solidifying his reputation as a leading researcher in the field of mathematics. His contributions to wave propagation and elasticity models have been cited extensively in top scientific journals, affirming the significance of his work in both theoretical and applied mathematics.

Research Focus

Dr. Ali Mubaraki’s research primarily focuses on wave propagation, elasticity, and surface waves in mathematical modeling. His work explores complex phenomena such as surface waves in coated elastic solids, wave solutions in porous media, and wave behaviors under fractional temporal variation. He also investigates applications in thermoelasticity, heat interactions, and the effects of external forces on wave propagation. Dr. Mubaraki employs asymptotic methods to model wave behavior in various materials, providing valuable insights into the mechanical properties of solids under different conditions. His research extends to the analysis of solitons, nonlinear dynamics, and the effects of external fields like magnetic forces and gravitational forces. Dr. Mubaraki’s contributions are advancing both theoretical and applied mathematics, particularly in the fields of elasticity and wave propagation.

Publications

  1. Wave propagation in an elastic coaxial hollow cylinder when exposed to thermal heating and external load 📚
  2. Wave solutions and numerical validation for the coupled reaction-advection-diffusion dynamical model in a porous medium 📐
  3. Effect of fractional temporal variation on the vibration of waves on elastic substrates with spatial non-homogeneity 🌊
  4. Additional solitonic and other analytical solutions for the higher-order Boussinesq-Burgers equation 📝
  5. Explicit model for surface waves on an elastic half-space coated by a thin vertically inhomogeneous layer 🔬
  6. Surface wave propagation in a rotating doubly coated nonhomogeneous half space with application 🌐
  7. Homoclinic breathers and soliton propagations for the nonlinear (3+1)-dimensional Geng dynamical equation 🚀
  8. Heat and wave interactions in a thermoelastic coaxial solid cylinder driven by laser heating sources 🌞
  9. Propagation of surface waves in a rotating coated viscoelastic half-space under the influence of magnetic field and gravitational forces ⚛️
  10. Modeling the dispersion of waves on a loaded bi-elastic cylindrical tube with variable material constituents 🧲
  11. On Rayleigh wave field induced by surface stresses under the effect of gravity 🌍
  12. Asymptotic models for surface waves in coated elastic solids 📏
  13. Pulse-driven robot: motion via distinct lumps and rogue waves 🤖
  14. Surface waves on a coated homogeneous half-space under the effects of external forces 🌐
  15. Analysis of horizontally polarized shear waves on a highly inhomogeneous loaded bi-material plate 📊
  16. Closed-form asymptotic solution for the transport of chlorine concentration in composite pipes 🚰
  17. Optical devices: motion via breathers, rogue waves and rational solitons 💡
  18. Modeling the dispersion of waves in a multilayered inhomogeneous membrane with fractional-order infusion 🧬
  19. A New Class of Coordinated Non-Convex Fuzzy-Number-Valued Mappings with Related Inequalities and Their Applications 🧠
  20. Asymptotic Consideration of Rayleigh Waves on a Coated Orthorhombic Elastic Half-Space Reinforced Using an Elastic Winkler Foundation 📐

 

Lilyana Khatib | Rehabilitation | Best Researcher Award

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Ms. Lilyana Khatib | Rehabilitation | Best Researcher Award

Researcher, University of Haifa, Israel.

Lilyana Khatib is a passionate and skilled Machine Learning (ML) Algorithm Engineer with a focus on machine and deep learning algorithms. Holding a Master’s degree in Computer Science, she specializes in applying advanced machine learning techniques to real-world challenges, particularly in the healthcare and medical fields. She is known for her quick learning ability and disciplined approach to problem-solving. In her current role at Biosense Webster, Lilyana is involved in developing algorithms for electrophysiology and cardiac rhythm, contributing to the advancement of medical technology. Beyond her professional work, she is actively engaged in volunteering efforts, including mentoring and empowering Arab women in STEM and exposing high-school students to the world of technology. Her research interests also extend to adaptive testing systems and computer vision applications.

Profile

Scopus

Education 

Lilyana Khatib completed her M.Sc. in Computer Science at the University of Haifa, graduating with a GPA of 95, cum laude. During her studies, she focused on machine learning and its applications in various domains, including healthcare. She pursued a Deep Learning course at the Technion, where she achieved an impressive grade of 97, demonstrating her mastery in the field. Her academic career was marked by a commitment to excellence, combining theoretical knowledge with practical research. Her B.Sc. in Computer Science from the University of Haifa, with a GPA of 83, laid the foundation for her deep interest in artificial intelligence and machine learning. Lilyana’s academic training enabled her to conduct high-impact research, such as her thesis on adaptive testing for fall risk assessments. She continues to build on this foundation through her professional work and volunteer initiatives.

Experience 

Lilyana Khatib’s professional experience spans across various aspects of machine learning and algorithm development. Currently working as a Machine Learning Algorithm Engineer at Biosense Webster since 2022, Lilyana designs and implements ML algorithms, addressing challenges in electrophysiology and cardiac rhythm. She manages end-to-end ML pipelines, including data collection, feature engineering, model development, and evaluation. In this role, she collaborates with multidisciplinary teams, including hardware, software, and clinical experts, to integrate algorithms seamlessly. Prior to this, she worked as a Research Assistant at Bar Ilan University, contributing to ML research on sign language recognition and motion capture analysis. Additionally, she served as a Teaching Assistant at the University of Haifa, tutoring computer science students and creating AI lab exercises. Lilyana’s diverse experiences allow her to approach problems with both academic rigor and practical insight, making her a versatile contributor to machine learning projects.

Awards and Honors 

Lilyana Khatib has received several academic and professional accolades throughout her career. She graduated with distinction (cum laude) from the University of Haifa with a Master’s degree in Computer Science, reflecting her strong academic performance and dedication to excellence. Her research contributions have also earned recognition in the field of machine learning, with her work on adaptive testing algorithms for older adults being published in Applied Sciences. In addition, her participation in international conferences such as the Language Resources and Evaluation Conference (LREC) in Marseilles, France, where she co-authored a paper on sentiment analysis, further highlights her standing in the research community. Beyond academic awards, Lilyana is also celebrated for her leadership roles, especially in mentoring and empowering underrepresented groups in STEM, such as her involvement as a team lead at AWSc and a mentor at Tsofen, showcasing her commitment to fostering diversity and inclusion in technology.

Research Focus 

Lilyana Khatib’s research focuses on the intersection of machine learning, healthcare, and computer vision. Her primary area of interest lies in developing advanced algorithms for healthcare applications, specifically in cardiac rhythm analysis, electrophysiology, and fall risk assessments. Through her work at Biosense Webster, she applies both classic machine learning and deep learning techniques to real-world challenges in the medical field, improving patient outcomes through more accurate diagnostics and assessments. Lilyana’s M.Sc. thesis, which explored a machine learning-based computerized adaptive testing algorithm for fall risk, demonstrates her dedication to healthcare technology. Additionally, she has worked on projects such as the Crying Detection Application, which uses computer vision to detect emotional states without relying on audio. Her research is highly interdisciplinary, integrating computer science, healthcare, and AI, and aims to make a meaningful impact on medical practices and patient care, particularly for vulnerable populations such as older adults.

Publications

  • Using Machine Learning to Shorten and Adapt Fall Risk Assessments for Older Adults 🧠📊 (Applied Sciences, 2025)
  • Capturing Distalization 📖 (Workshop on Sentiment Analysis and Linguistic, LREC, Marseilles, France, 2022)

Vladimir Rovenski | Differential geometry | Best Researcher Award

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Prof. Dr. Vladimir Rovenski | Differential geometry | Best Researcher Award

Full Professor, University of Haifa, Israel.

Professor Vladimir Rovenski, born May 12, 1953, in Karaganda (Kazakhstan, USSR), is a distinguished mathematician. He has been a professor emeritus at the University of Haifa since 2021, having held various academic positions, including full professor at the University of Haifa and senior scientist at Technion. Rovenski’s research spans differential geometry, topology, applied mathematics, and mathematical modeling. Over his career, he has contributed to the study of foliations, curvature, and anisotropic elasticity. He has published over 195 papers and 14 books and organized multiple international conferences. Rovenski is also a guest editor for numerous special issues in mathematics journals. He remains an active contributor to the academic community with extensive involvement in international projects and conferences.

Profile 

Google scholar

Orcid

Education

Professor Rovenski obtained his M.Sc. degree in 1976, Ph.D. in 1985, and D.Sci. in 1994. His academic journey began with a focus on geometry and topology, particularly foliations and curvatures. His M.Sc. thesis on quasi-affine functions and programming was supervised by Prof. G.S. Rubinshtein. His Ph.D. dissertation focused on uniquely projecting surfaces in spheres and projective spaces, guided by Prof. V.A. Toponogov. His D.Sci. dissertation, on geometry and topology of foliations, advanced research on nonnegative curvature in mixed directions. Rovenski earned prestigious diplomas, including Correspondent Member of the Academy of Natural Sciences (1995) and Full Professor (1996).

Experience

Professor Rovenski’s academic career spans several prestigious institutions. He served as a full professor at the University of Haifa from 2004 to 2021, and as a senior scientist at Technion, Israel Institute of Technology, from 1999 to 2004. Before moving to Israel, he was a professor at the State Pedagogical University in Krasnoyarsk, USSR, and at Karaganda State University. His early academic experience also included work at Siberian Building Institute and Karaganda State Polytechnic Institute. Rovenski has been active in supervising postdoctoral students and has organized several international mathematical workshops and conferences. His extensive career reflects a commitment to research, teaching, and advancing mathematical knowledge globally.

Awards and Honors

Professor Rovenski has received numerous awards and honors throughout his career. In 1994, he was awarded the Russian Fund of Fundamental Investigations grant for his work on the geometry and topology of foliations with nonnegative curvature. He was supported by Marie Curie Actions grants between 2008 and 2014 for his work on extrinsic geometry of foliations. He is a long-standing member of the American Mathematical Society (AMS), the Israel Mathematical Union (IMU), and the European Mathematical Society (EMS). Rovenski has also received invitations to visit several universities as a guest professor, further solidifying his reputation as a leading expert in the field.

Research Focus

Professor Rovenski’s primary research interests include differential geometry, topology of submanifolds and foliations, anisotropic elasticity, and piezoelectricity. His work on extrinsic geometry of foliations led to the development of “extrinsic geometric flows,” an innovative method to study foliations with variable adapted metrics. He has explored the Ricci flow on foliated manifolds and the geometry of codimension-one foliations. Rovenski has also contributed to modeling and teaching mathematics using computational tools like MAPLE and MATLAB. His work integrates theoretical developments in geometry with practical applications in engineering, physics, and material science.

Publications

  • Analytical methods in anisotropic elasticity: with symbolic computational tools 📘
  • Foliations on Riemannian manifolds and submanifolds 📚
  • Geometry of Curves and Surfaces with MAPLE 📐
  • Topics in extrinsic geometry of codimension-one foliations 🔎
  • Modeling of Curves and Surfaces with MATLAB® 📊
  • Integral formulae on foliated symmetric spaces 📜
  • Extrinsic geometry of foliations 🧩
  • An example of Lichnerowicz-type Laplacian 📝
  • Mirzakhani’s curve counting and geodesic currents 🔄
  • Integral formulae for a Riemannian manifold with two orthogonal distributions ➗
  • Deforming metrics of foliations 🔄
  • Saint-Venant’s problem for homogeneous piezoelectric beams ⚡
  • Variations of the total mixed scalar curvature of a distribution 🔠
  • On solutions to equations with partial Ricci curvature 🔍
  • New metric structures on g-foliations 🔑
  • Mixed gravitational field equations on globally hyperbolic spacetimes 🌌
  • Almost -Ricci solitons on Kenmotsu manifolds 💫
  • On the rigidity of the Sasakian structure and characterization of cosymplectic manifolds 🧩
  • Integral formulas for a metric-affine manifold with two complementary orthogonal distributions 📏
  • Integral formulas for a Riemannian manifold with several orthogonal complementary distributions 📐