Mr. Abdullah Al Mamun | Deep Learning | Young Scientist Award

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Mr. Abdullah Al Mamun | Deep Learning | Young Scientist Award

Lecturer, Dhaka University of Engineering & Technology (DUET), Gazipur, Bangladesh

Abdullah Al Mamun is a passionate researcher and academic professional specializing in Internet of Things (IoT), Machine Learning 🤖, and Explainable Artificial Intelligence (XAI). Currently pursuing his Master of Science in Engineering at Dhaka University of Engineering & Technology (DUET), Gazipur, he brings a vibrant combination of theoretical knowledge and hands-on research experience. His dynamic involvement in projects across sustainability, computer vision 🧠, and intelligent systems has positioned him as a promising contributor to the technology and research domain.

Publication Profile

ORCID

🎓 Education Background

Abdullah Al Mamun is presently pursuing his M.Sc. in Computer Science and Engineering at DUET, Gazipur (since October 2024), where he has already completed his Bachelor of Science in Computer Science and Engineering with distinction in 2024 🎓. His consistent academic journey showcases his dedication to computing, innovation, and advanced research.

💼 Professional Experience

Mamun is currently working as a Lecturer at the Department of CSE, Model Institute of Science and Technology, Gazipur, while also serving as a part-time Research Assistant in the Multimedia Signal & Image Processing research group at Woosong University, South Korea 🌏. With three years of tutoring experience at ACME DUET Admission Coaching Center, and two internships in web development and CMS technologies, he has gained broad teaching, mentoring, and development experience across various platforms 🖥️. His administrative roles in DUET Career & Research Club and DUET Computer Society also underscore his leadership and community contributions.

🏆 Awards and Honors

Abdullah has been recognized for his academic and problem-solving excellence. He earned the “Second Runner-Up” at BEYOND THE METRICS-2023 hosted by IUT (OIC), and “Runner-Up” at the Intra DUET Programming Contest (IDPC) 2022 🏅. He has actively participated in events like NASA Space App Challenge 2024 and DUET TECH FEST-2023, reflecting his engagement in competitive and innovation-driven activities 🚀.

🔬 Research Focus

Abdullah’s core research interests lie in IoT and sustainability, Machine Learning, Computer Vision, Explainable AI, and Reinforcement Learning 🧠📡. He has been instrumental in implementing real-world projects such as IoT-based energy monitoring systems and child safety monitoring, defect detection via XAI, and skin cancer classification using optimized deep learning models. His collaborative projects with global research teams exhibit his strong contribution to the evolving field of intelligent systems and digital transformation.

✅ Conclusion

With an impressive blend of academic rigor, technical skills, and collaborative research experience, Abdullah Al Mamun is making impactful strides in the field of computer science 🧩. His work exemplifies innovation, sustainability, and intelligence in engineering systems. He continues to grow as a researcher dedicated to contributing to global scientific advancements 🌐.

📚 Top Publications 

  1. Developed an IoT-based Smart Solar Energy Monitoring System for Environmental Sustainability – 3rd International Conference on Advancement in Electrical and Electronic Engineering, 2024.
    Cited by: 7 articles 📑

  2. Developing an IoT-based Child Safety and Monitoring System: An Efficient Approach – IEEE 26th International Conference on Computer and Information Technology (ICCIT), 2023.
    Cited by: 13 articles 🔐

  3. Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques – IEEE Journal, 2024.
    Cited by: 15 articles ⚙️

  4. IoT-Based Solutions for Uneven Roads and Balanced Vehicle Systems Using YOLOv8 – MDPI Sensors Journal, 2023.
    Cited by: 10 articles 🚗

  5. Optimizing Deep Learning for Skin Cancer Classification: A Computationally Efficient CNN – 2nd NCIM Conference, Bangladesh, 2024.
    Cited by: 5 articles 🧬

  6. Enhancing DBSCAN Dynamically: A Novel Approach to Parameter Initialization and Outlier Reduction – Bachelor Thesis, DUET, 2024.
    Cited by: 3 articles 🔍

 

Prof. Dr. Jörg Schäfer | Machine Learning | Best Researcher Award

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Prof. Dr. Jörg Schäfer | Machine Learning | Best Researcher Award

Professor, Frankfurt University of Applied Sciences, Germany

Professor Dr. Jörg Schäfer is a renowned academic and researcher in the field of Computer Science, currently serving at the Frankfurt University of Applied Sciences in Germany. With a distinguished background in mathematics and a dynamic career bridging academia and industry, Dr. Schäfer is celebrated for his expertise in object-oriented programming, distributed systems, databases, and machine learning. His innovative research in artificial intelligence and human activity recognition, paired with decades of experience in technology strategy and complex system architecture, have made him a leading figure in both academic and professional circles.

Publication Profile

🎓 Education Background:

Dr. Schäfer completed his Ph.D. in Mathematics with summa cum laude at Ruhr-Universität Bochum (1991–1993) under the supervision of Prof. Dr. Sergio Albeverio. His doctoral work was part of the elite DFG graduate program “Geometrie und Mathematische Physik” and included an academic travel scholarship to Japan. Before his Ph.D., he earned a diploma in Mathematical Physics with distinction from Ruhr-Universität Bochum (1987–1991), laying the groundwork for his future interdisciplinary research.

💼 Professional Experience:

Dr. Schäfer’s professional career blends deep academic involvement with high-impact industry roles. Since 2009, he has been a professor at Frankfurt University of Applied Sciences, teaching subjects such as object-oriented programming, distributed systems, and machine learning. He is the founding member of the Industrial Data Science (INDAS) research group and serves as Chairman of the B.Sc. Computer Science program. Prior to his academic tenure, Dr. Schäfer held senior positions at Accenture (2005–2009) and Cambridge Technology Partners (2000–2005), where he was responsible for large-scale architecture design, pre-sales, delivery, and enterprise integration strategies. His early career includes project management roles at Westdeutsche Landesbank and a trainee program at Salomon Brothers, as well as scientific assistant roles focused on stochastic analysis.

🏅 Awards and Honors:

Professor Schäfer has received several prestigious accolades throughout his career. Most notably, he was awarded the Hessischer Hochschulpreis in 2022 for excellence in teaching. During his academic formation, he was also a scholar of the Studienstiftung des deutschen Volkes (1987–1991), reflecting his outstanding academic promise from an early stage.

🔬 Research Focus:

Dr. Schäfer’s research is focused on artificial intelligence, machine learning, mobile and distributed systems, and human activity recognition. His work leverages WiFi channel state information (CSI) for device-free activity detection, contributing significantly to the field of pervasive computing. He also has a foundational background in mathematical physics, particularly in Chern–Simons theory and stochastic analysis, which informs his unique approach to computer science problems.

🧩 Conclusion:

With a remarkable blend of academic rigor and real-world application, Professor Dr. Jörg Schäfer stands out as a multifaceted scholar and technology leader. His research continues to shape the future of data science and AI-driven systems, while his dedication to teaching and mentorship inspires the next generation of computer scientists.

📚 Top Publications

  1. Computer-implemented method for ensuring the privacy of a user, computer program product, device
    J Schäfer, D Toma
    US Patent 8,406,988, 2013
    Cited by: 237 articles

  2. Device free human activity and fall recognition using WiFi channel state information (CSI)
    N Damodaran, E Haruni, M Kokhkharova, J Schäfer
    CCF Transactions on Pervasive Computing and Interaction, 2020
    Cited by: 109 articles

  3. Human activity recognition using CSI information with nexmon
    J Schäfer, BR Barrsiwal, M Kokhkharova, H Adil, J Liebehenschel
    Applied Sciences, 2021
    Cited by: 75 articles

  4. Abelian Chern–Simons theory and linking numbers via oscillatory integrals
    S Albeverio, J Schäfer
    Journal of Mathematical Physics, 1995
    Cited by: 53 articles

  5. A rigorous construction of Abelian Chern-Simons path integrals using white noise analysis
    P Leukert, J Schäfer
    Reviews in Mathematical Physics, 1996
    Cited by: 43 articles

  6. Fall detection from electrocardiogram (ECG) signals and classification by deep transfer learning
    FS Butt, L La Blunda, MF Wagner, J Schäfer, I Medina-Bulo, et al.
    Information, 2021
    Cited by: 40 articles

  7. Device free human activity recognition using WiFi channel state information
    N Damodaran, J Schäfer
    2019 IEEE SmartWorld Conference
    Cited by: 37 articles

  8. Cloud computing – Evolution in der Technik, Revolution im Business
    G Münzl, B Przywara, M Reti, J Schäfer, et al.
    Berlin: BITKOM, 2009
    Cited by: 37 articles

 

Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

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Mr. Muhammad Tauqeer Iqbal | Machine Learning | Best Researcher Award

Mr. Muhammad Tauqeer Iqbal , Yangzhou University, China

Iqbal Muhammad Tauqeer is a passionate researcher and master’s student at Yangzhou University, China , specializing in the domain of Machine Learning 🤖. With a solid foundation in both industry and academia, he has combined practical management experience with cutting-edge AI research. His dedication to data science applications and computer vision has led to a notable publication recognized as a best paper, showcasing his potential in the rapidly evolving tech landscape 🌟.

Professional Profile

ORCID

🎓 Education Background

Iqbal is currently pursuing his Master’s degree at Yangzhou University, China 📚, where his academic focus is on machine learning and its applications in computer vision. His academic pursuits have been driven by a commitment to advancing AI-driven solutions in environmental monitoring and digital recognition systems.

💼 Professional Experience

Before his transition into research, Iqbal gained valuable industry experience as an Assistant Production Manager at OPPO Mobile Company Pakistan 📱 for over two years. This role provided him with deep insights into production workflows and industry standards, bridging the gap between theoretical learning and practical application.

🏆 Awards and Honors

Iqbal’s research has already earned accolades, with his paper titled “A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy” being recognized as a Best Paper 🥇. This early recognition is a testament to the impact and novelty of his contributions to AI-powered environmental diagnostics.

🔬 Research Focus

His research interests lie primarily in Machine Learning, Deep Learning, Transfer Learning, and Computer Vision 🧠📊. He is particularly focused on applying these techniques to UV–Vis Spectroscopy and digital display recognition. He is currently working on a second research project that extends his work in pattern recognition and visual AI.

🔚 Conclusion

With a unique blend of industrial management experience and academic rigor, Iqbal Muhammad Tauqeer is emerging as a promising contributor to the field of Artificial Intelligence. His work in machine learning models for environmental monitoring reflects not only his technical skills but also his commitment to impactful innovation 🌍🔍.

📚 Publication Top Note

  1. Title: A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy
    Journal: Journal of Imaging
    Publisher: MDPI
    Published Year: 2025

 

Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

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Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

Student, Guangxi University, China

Pingjie Ou is a passionate master’s student at Guangxi University, China, specializing in edge computing, cloud computing, and machine learning. With a strong academic foundation and growing research portfolio, he is actively contributing to next-generation computing paradigms. His early contributions in deep reinforcement learning applications for vehicular networks have already gained traction within the academic community. 🧠💡

Professional Profile

Scopus

🎓 Education Background

Pingjie Ou is currently pursuing his master’s degree at Guangxi University, one of the prominent institutions in China. His academic focus lies in electrical and computer engineering, with emphasis on distributed computing and artificial intelligence. 📘🏫

💼 Professional Experience

Although a student, Pingjie Ou has engaged in substantial research activities under funded projects including The National Natural Science Foundation of China (No. 62162003) and GuikeZY24212059 supported by the Guangxi Province. His active involvement in real-time research scenarios demonstrates promising professional potential. 🔬📊

🏅 Awards and Honors

As an emerging scholar, Pingjie Ou has not yet accumulated major awards but has gained recognition through impactful publications and research citations. His growing citation record and h-index reflect the potential for future accolades. 🏆📈

🔍 Research Focus

His core research interests include edge computing, cloud computing, vehicular networks, and machine learning. He is particularly focused on cooperative caching, resource management, and optimizing network efficiency using artificial intelligence approaches such as deep reinforcement learning. 🚗☁️📶

🧾 Conclusion

Pingjie Ou is a driven young researcher dedicated to advancing intelligent computing technologies. With strong academic grounding, collaborative research exposure, and early citation impact, he stands as a promising candidate for recognition in the domain of computer science and engineering. His scholarly journey is on a clear upward trajectory. 🚀📚

📚 Publication Top Note

  1. PDRL-CM: An efficient cooperative caching management method for vehicular networks based on deep reinforcement learning
    📅 Published Year: 2025
    📖 Journal: Ad Hoc Networks
    🔗 10.1016/j.adhoc.2025.103888

 

Mr. Jun Yin | Circuit design | Best Researcher Award

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Mr. Jun Yin | Circuit design | Best Researcher Award

PhD Student, University of Virginia, United States

Jun Yin is a dedicated Ph.D. candidate in Electrical Engineering at the University of Virginia, with a robust academic and professional background in VLSI design, low-power circuits, and memory systems. With experience spanning top research institutions and the semiconductor industry, Jun’s work bridges theoretical research and practical innovation, focusing on emerging chip designs and system-level efficiency. His efforts have already earned recognition in international conferences and high-impact journals, making him a rising figure in the field of electrical and computer engineering.

Professional Profile

Google Scholar

ORCID

Scopus

🎓 Education Background:

Jun holds a Ph.D. (2021–2025, GPA 3.925/4.0) and a Master’s degree (2021–2023, GPA 3.925/4.0) in Electrical Engineering from the University of Virginia, USA. Before that, he completed his M.Sc. in Materials Science at Tsinghua University (2016–2019, GPA 3.77/4.0), one of China’s top institutions. He began his academic journey with a B.Eng. in Material Engineering from Qinghai University (2012–2016), where he graduated with an impressive GPA of 89/100.

💼 Professional Experience:

Jun is currently interning at MediaTek USA Inc., Austin, TX, working on advanced memory circuit design using leading technologies such as TSMC N3E and N2P. His work includes SRAM library generation, margin verification, and design optimization using tools like NanoTime and XA. Previously, Jun contributed to FPGA and ASIC design projects at the University of Virginia and worked on neural network accelerators at UMass Amherst, achieving notable results such as a 99.5% fabrication yield and 93.63% classification accuracy. He has also served as a teaching assistant for graduate-level courses in digital design.

🏆 Awards and Honors:

Jun has received several honors for his outstanding contributions to research, including being named a Young Fellow at the 58th Design Automation Conference (DAC) in 2021. He also earned the Dean’s Fellowship at UMass Amherst in 2020, recognizing his academic excellence and research potential in the field of engineering.

🔬 Research Focus:

Jun’s research spans VLSI physical design, low-power SRAM circuits, RF energy harvesting systems, and AI hardware accelerators. He has developed innovative techniques in leakage suppression and impedance matching for IoT and CRFID applications. His current work at the University of Virginia focuses on system-on-chip solutions for energy-constrained environments and has led to publications in top IEEE conferences like ISCAS and ISQED. Additionally, his past work on memristor-based systems contributed to high-impact journals and breakthroughs in neural hardware.

🔚 Conclusion:

Jun Yin exemplifies a new generation of interdisciplinary researchers who blend academic excellence with industry-ready skills. With a proven publication record, practical experience in advanced semiconductor technologies, and a passion for circuit innovation, he is poised to make significant contributions to the future of low-power and intelligent electronic systems.

📚 Top Publications with Citation Details:

  1. A Low Power SRAM with Fully Dynamic Leakage Suppression for IoT Nodes – IEEE ISQED, 2023
    Cited by: 2 articles

  2. Adaptive crystallite kinetics in homogenous bilayer oxide memristor for emulating diverse synaptic plasticity – Advanced Functional Materials, 2018
    Cited by: 181 articles

  3. Competition between Metallic and Vacancy Defect Conductive Filaments in a CH3NH3PbI3-Based Memory Device – Journal of Physical Chemistry C, 2018
    Cited by: 157 articles

  4. Guiding the growth of a conductive filament by nanoindentation to improve resistive switching – ACS Applied Materials & Interfaces, 2017
    Cited by: 135 articles

  5. Performance‐enhancing selector via symmetrical multilayer design – Advanced Functional Materials, 2019
    Cited by: 88 articles

  6. A fully hardware-based memristive multilayer neural network – Science Advances, 2021
    Cited by: 78 articles

  7. Modulating metallic conductive filaments via bilayer oxides in resistive switching memory – Applied Physics Letters, 2019
    Cited by: 55 articles

  8. Phase-change nanoclusters embedded in a memristor for simulating synaptic learning – Nanoscale, 2019
    Cited by: 32 articles

 

Dr. Tewodros Yosef | Computational Geotechnics | Best Researcher Award

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Dr. Tewodros Yosef | Computational Geotechnics | Best Researcher Award

Research Assistant Professor, Midwest Roadside Safety Facility, University of Nebraska-Lincoln, United States.

Dr. Tewodros Y. Yosef is a distinguished Research Assistant Professor in the Department of Civil and Environmental Engineering at the University of Nebraska–Lincoln 🌍. With a strong foundation in computational geomechanics and impact dynamics, Dr. Yosef contributes significantly to cutting-edge research in geotechnical and structural engineering, especially under extreme conditions such as vehicular impact and environmental stress. With extensive experience at the Midwest Roadside Safety Facility, he blends experimental work with advanced numerical modeling to create resilient civil infrastructure systems across diverse environments 🏗️.

Professional Profile

Google Scholar

Scopus

🎓 Education Background

Dr. Yosef earned his Ph.D. in Civil Engineering from the University of Nebraska–Lincoln in 2021 🎓, with a focus on Geotechnical and Materials Engineering. His doctoral dissertation centered on modeling the impact dynamics of pile-granular soil systems. He also holds an M.S. in Civil Engineering from the University of Mississippi (2015) with a thesis on hydro-thermal analysis of geostructures 🌡️, and a B.S. in Civil Engineering from Addis Ababa University (2011), specializing in structural mechanics 🏛️.

💼 Professional Experience

Dr. Yosef began his career as an Assistant Lecturer at Addis Ababa University 🇪🇹 before transitioning to graduate-level research in the U.S. He served in multiple research assistant roles at the University of Mississippi and the University of Nebraska–Lincoln, advancing to Postdoctoral Research Associate and then to his current position as Research Assistant Professor at the Midwest Roadside Safety Facility 👨‍🏫. His responsibilities include the design and numerical analysis of transportation safety structures, dynamic modeling of geomaterials, and collaborative research with national transportation bodies.

🏆 Awards and Honors

Dr. Yosef has received numerous awards recognizing his academic excellence and research impact 🥇. Notably, he won the 2023 Outstanding Postdoc Award and the 2021 TRB AKD20 Best Paper Award. Other accolades include fellowships from Milton Mohr, Peck/Benak Engineering, and the Ethiopian Geophysical Union. He has also been awarded competitive scholarships and travel grants from institutions including the University of Nebraska and University of Mississippi ✨.

🔬 Research Focus

Dr. Yosef’s research integrates computational modeling, experimental testing, and artificial intelligence to advance geotechnical and structural engineering 📊. He specializes in large deformation analysis, impact-resistant structures, and resilient transportation systems under extreme loading conditions like vehicular crashes, flooding, freezing, and thawing ❄️💥. He also pioneers the use of coupled FEM-SPH and FEM-ALE techniques in simulating soil-structure interaction and crashworthiness of infrastructure components.

📚Citations:

📚 Citations: 132 ( by 93 documents )
📄 Publications: 20 ( Documents )
📊 h-index: 6

🧾 Conclusion

With a unique combination of theoretical depth and practical engineering application, Dr. Tewodros Y. Yosef is a rising leader in civil infrastructure resilience and geotechnical simulation. His multidisciplinary expertise continues to shape the future of transportation safety and geotechnical innovation in both academic and applied contexts 🚀.

📚 Top Publications Notes

  1. Computational modeling and dynamic response of highway bridge columns subjected to combined vehicle collision and air blast
    Published in: Engineering Failure Analysis, 2021
    Cited by: 37 articles

  2. Seepage monitoring of an embankment dam based on hydro-thermal coupled analysis
    Published in: Journal of Engineering Materials and Technology, 2017
    Cited by: 23 articles

  3. Hydro-thermal coupled analysis for health monitoring of embankment dams
    Published in: Acta Geotechnica, 2018
    Cited by: 20 articles

  4. Numerical modeling and performance assessment of bridge column strengthened by FRP and polyurea under combined collision and blast loading
    Published in: Journal of Composites for Construction, 2022
    Cited by: 19 articles

  5. Residual axial capacity estimates for bridge columns subjected to combined vehicle collision and air blast
    Published in: Journal of Bridge Engineering, 2021
    Cited by: 14 articles

  6. A multi-material ALE model for investigating impact dynamics of pile-soil systems
    Published in: Soil Dynamics and Earthquake Engineering, 2023
    Cited by: 10 articles

  7. Seepage-heat coupled analysis for estimating phreatic line of an earth dam from temperature profile
    Published in: Symposium on the Application of Geophysics to Engineering and Environmental Problems, 2015
    Cited by: 7 articles

 

Wai Yie Leong | Data Science | Best Researcher Award

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Prof. Dr. Wai Yie Leong | Data Science | Best Researcher Award

Senior Professor at INTI International University, Malaysia

IR. Prof. Dr. Leong Wai Yie is a distinguished researcher and academic leader in electrical engineering, with a Ph.D. from The University of Queensland, Australia. She specializes in smart sensor networks, AI, big data analytics, and sustainable city technologies. A Fellow of IET (UK) and IEM, she has held senior positions at top Malaysian universities and contributed significantly to research excellence, program accreditation, and innovation. She has secured international research grants, published widely in high-impact journals, and received multiple Best Paper Awards. Her work bridges academia and industry, advancing cutting-edge solutions in healthcare, engineering, and Industry 4.0 systems.

📚Professional Profile

Orcid

Scopus

Google Scholar

🎓Academic Background

IR. Prof. Dr. Leong Wai Yie holds a strong academic foundation in electrical engineering. She earned her Bachelor’s degree with First Class Honours in Electrical Engineering from The University of Queensland, Australia, in 2001. Continuing her academic excellence, she completed her Ph.D. in Electrical Engineering at the same institution in 2005. Her educational journey provided a solid basis for her specialization in smart sensor systems, artificial intelligence, and data analytics. The rigorous training and research exposure during her studies laid the groundwork for her influential career in academia, research leadership, and multidisciplinary engineering innovation across international platforms.

💼Professional Experience

IR. Prof. Dr. Leong Wai Yie has over two decades of academic and research experience, holding senior roles in top institutions such as INTI International University, Perdana University, MAHSA University, and Taylors University. She has served as Dean, Director of Research Excellence, and Head of Department, contributing to academic program development, accreditation, and research strategy. Her earlier roles include project management at SIMTech, A*STAR Singapore, and lecturer positions at Imperial College London and The University of Queensland. Her experience bridges academia and industry, focusing on innovation, research commercialization, and the advancement of smart technologies and engineering education.

🏅Awards and Honors

IR. Prof. Dr. Leong Wai Yie has received numerous prestigious awards recognizing her research excellence and innovation. In 2024 alone, she earned multiple Best Paper Awards at international IEEE conferences in Taiwan, Thailand, Vietnam, and Japan. She also received the 2024 Travel Grant Award from the Institution of Engineering and Technology (UK). These accolades reflect her contributions to smart technologies, biomedical engineering, and sustainable systems. Her work has been consistently recognized for its originality, societal relevance, and technical impact, solidifying her reputation as a leading figure in engineering research both regionally and globally.

🔬Research Focus

IR. Prof. Dr. Leong Wai Yie’s research centers on emerging technologies with strong societal and industrial impact. Her primary areas include smart sensor networks, big data analytics, artificial intelligence, remote sensing, and sustainable city development. She is actively involved in advancing Industry 4.0 applications and international standards for engineering systems. Her interdisciplinary approach bridges biomedical engineering, environmental monitoring, and intelligent systems design. Through extensive collaboration with global institutions, she has developed innovative solutions in health diagnostics, aerospace tracking, and smart infrastructure. Her research aims to enhance quality of life through data-driven, intelligent, and sustainable technological advancements.

Citations:

📚 Citations: 1,022 (by 431 documents)
📄 Publications: 189 documents
📊 h-index: 16

📖Publication Top Notes

Potential and utilization of thermophiles and thermostable enzymes in biorefining
📅 Year: 2007 | Cited by: 781

Using indirect protein–protein interactions for protein complex prediction
📅 Year: 2008 | Cited by: 202

Endoglucanases: insights into thermostability for biofuel applications
📅 Year: 2013 | Cited by: 162

B-MYB is essential for normal cell cycle progression and chromosomal stability of embryonic stem cells
📅 Year: 2008 | Cited by: 123

Signal processing techniques for knowledge extraction and information fusion
📅 Year: 2008 | Cited by: 122

Current state and challenges of natural fibre-reinforced polymer composites as feeder in FDM-based 3D printing
📅 Year: 2021 | Cited by: 88

Markers of dengue severity: a systematic review of cytokines and chemokines
📅 Year: 2016 | Cited by: 67

A review of localization techniques in wireless sensor networks
📅 Year: 2023 | Cited by: 60

Convergence of IoT, Blockchain, and Computational Intelligence in Smart Cities
📅 Year: 2024 | Cited by: 51

The nine pillars of technologies for Industry 4.0
📅 Year: 2020 | Cited by: 50

✨Conclusion

Based on her exceptional academic credentials, interdisciplinary research expertise, international recognition, and sustained leadership in engineering innovation, IR. Prof. Dr. Leong Wai Yie stands out as a highly deserving candidate for the Best Researcher Award. With a Ph.D. from The University of Queensland and prestigious fellowships from IET, IEM, and IEEE, she has contributed significantly to cutting-edge fields such as smart sensor networks, AI, and sustainable technologies. Her impactful publications, global collaborations, extensive grant portfolio, and multiple Best Paper Awards in 2024 reflect ongoing excellence. She exemplifies the qualities of a world-class researcher with tangible societal and academic impact.

 

 

Mehmet Gesoğlu | Construction Materials | Best Researcher Award

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Assoc. Prof. Dr. Mehmet Gesoğlu | Construction Materials | Best Researcher Award

Assoc. Prof. Dr. Mehmet Gesoğlu at Gaziantep University, Turkey

Dr. Mehmet Gesoglu is a seasoned civil engineering expert with a strong academic and professional background in concrete technology and structural materials. He earned his B.Sc. from Gaziantep University and both M.Sc. and Ph.D. degrees from Bogazici University. With over two decades of experience, he has contributed significantly as a researcher, quality auditor, and project supervisor in concrete and earthquake-related studies. He has led and participated in numerous national and international research projects and has received multiple scientific publication awards from TÜBİTAK. His work focuses on high-performance concrete, sustainability, and structural safety, supported by extensive conference and journal publications.

📚Professional Profile

Scopus

Google Scholar

🎓Academic Background

Dr. Mehmet Gesoglu has a solid academic foundation in civil engineering, beginning with his B.Sc. degree from the Faculty of Engineering at Gaziantep University, completed between 1990 and 1995. He continued his postgraduate education at Bogazici University in Istanbul, earning his M.Sc. degree from the Institute of Science and Technology in 1998, followed by a Ph.D. in Civil Engineering in 2004. All of his academic training was conducted in English, reflecting his international orientation and proficiency. His educational background laid the groundwork for his later achievements in advanced concrete technology, material science, and structural engineering research.

💼Professional Experience

Dr. Mehmet Gesoglu has amassed extensive professional experience in civil engineering, particularly in concrete technology and structural evaluation. From 1997 to 2004, he served as a Certified Quality Auditor for the Turkish Ready Mixed Concrete Association (THBB) while also working as a research assistant at Bogazici University. Between 2004 and 2016, he acted as the Chief Quality Auditor for THBB, overseeing concrete plants in Eastern and Southeastern Turkey. He has also been actively involved in national research projects and post-earthquake assessments, contributing to damage analysis, material testing, and structural strengthening. His work combines academic insight with practical field expertise.

🏅Awards and Honors

Dr. Mehmet Gesoglu has received numerous prestigious awards in recognition of his scientific contributions. He was awarded a scholarship by the Turkish Higher Education Council for his Ph.D. studies from 1996 to 2004. He received scientific publication awards from the Bogazici University Foundation in 2002, 2003, and 2004. Between 2006 and 2015, he was honored annually by TÜBİTAK (The Scientific and Technological Research Council of Turkey) for his impactful publications. These accolades reflect his sustained research excellence and significant contributions to the field of civil engineering, particularly in concrete technology and construction material science.

🔬 Research Focus

Dr. Mehmet Gesoglu’s research primarily centers on concrete technology, durability, and sustainable construction materials. His work explores high-performance concrete, lightweight aggregates, pozzolanic materials like fly ash and metakaolin, and the mechanical properties of reinforced and self-compacting concrete. He has contributed extensively to studies on fire resistance, structural damage assessment post-earthquake, and the development of innovative concrete mixtures using recycled and industrial by-products. His research also includes finite element modeling, interface zone characterization, and cold-bonded aggregate production. Through both experimental and analytical methods, Dr. Gesoglu advances practical solutions for improving concrete performance and structural resilience.

Citations:

📚 Citations: 7,204 (by 5,336 documents)
📄 Publications: 81 documents
📊 h-index: 49

📖Publication Top Notes

Cited by 635 | Year: 2004

Cited by 546 | Year: 2009

Cited by 398 | Year: 2012

Cited by 396 | Year: 2008

Cited by 351 | Year: 2012

Cited by 299 | Year: 2010

Cited by 258 | Year: 2014

✨Conclusion

Dr. Mehmet Gesoglu is a distinguished civil engineering researcher recognized for his extensive contributions to concrete technology, sustainable construction, and structural performance. With a Ph.D. from Bogazici University, he has led numerous national and international research projects, particularly in high-performance and eco-friendly concrete. His work bridges academia and industry through active roles in technical committees and quality control efforts. Honored repeatedly by TÜBİTAK for scientific excellence, Dr. Gesoglu’s research in earthquake resilience, recycled materials, and fire-damaged structures underscores his impact on infrastructure safety and sustainability. His leadership, innovation, and societal contributions make him a deserving recipient of the Best Researcher Award.

 

 

Mrs. Yun Soobeen | Medicine | Best Researcher Award

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Mrs. Yun Soobeen | Medicine | Best Researcher Award

resident, Gachon University Gil Medical Center Dentistry, South Korea

Dr. Soobeen Yun is a dedicated dental professional currently serving as a Resident in the Department of Oral and Maxillofacial Surgery at Gachon University Gil Medical Center Dentistry 🇰🇷. With a strong academic foundation and a growing research portfolio, Dr. Yun is emerging as a promising figure in the field of oral surgery. Her passion for clinical excellence and academic inquiry is reflected in her involvement in advanced implantology research and case-based studies.

Publication Profile

ORCID

🎓 Education Background:

Dr. Yun completed her Doctor of Dental Surgery (D.D.S.) degree from Chosun University, College of Dentistry between 2016 and 2022 🎓. Her academic training laid a solid groundwork for her subsequent residency in oral and maxillofacial surgery, enabling her to combine theoretical knowledge with practical surgical experience.

💼 Professional Experience:

Currently, Dr. Yun holds a Resident position at Gachon University Gil Hospital in Incheon, South Korea 🏥, where she works in the Oral and Maxillofacial Surgery department. Her clinical duties are complemented by her active involvement in academic research, collaborative studies, and surgical innovation.

🏆 Awards and Honors:

Though early in her career, Dr. Yun’s scholarly work and professional promise are positioning her for recognition in her field 🌟. She has already contributed to reputable journal publications and continues to engage in research that improves surgical accuracy and patient outcomes, qualifying her as a strong candidate for emerging researcher awards.

🔬 Research Focus:

Dr. Yun focuses on guided implant surgery, maxillofacial trauma, and post-surgical rehabilitation using advanced techniques such as fibula free flaps 🦷🔍. Her current ongoing research is centered on evaluating the accuracy of guided implant surgery, contributing to improving the predictability and safety of oral surgical procedures.

🔚 Conclusion:

With a mix of clinical rigor, scholarly contributions, and an evolving research profile, Dr. Soobeen Yun exemplifies the qualities of a rising talent in oral and maxillofacial surgery 🥼📈. Her journey reflects commitment, innovation, and a deep desire to impact dental medicine through both hands-on care and academic excellence.

📚 Top Publications 

  1. 🔗 Errors in guided dental implant placement on inclined surfaces with fully-guided systems

    • 🗓 Published: 2025

    • 📘 British Journal of Oral and Maxillofacial Surgery

    • 📈 Cited by: 4 articles (as of latest data)

    • 🧠 Notes: This study highlights common error margins in implant placement when performed on sloped surfaces, guiding improvements in digital surgery protocols.

  2. 🔗 Mandibular Rehabilitation with Fibula Free Flap and Dental Implant: A 4-Year Follow–up

    • 🗓 Published: 2024

    • 📘 Journal of Implantology and Applied Sciences

    • 📈 Cited by: 2 articles

    • 🧠 Notes: This long-term follow-up study showcases the successful rehabilitation of mandibular defects using fibula free flap technique and subsequent dental implants.

  3. 🔗 Refracture at the same area after zygomaticomaxillary complex fracture surgery: a case report

    • 🗓 Published: 2023

    • 📘 Oral Biology Research

    • 📈 Cited by: 3 articles

    • 🧠 Notes: A rare case of post-operative refracture is detailed with clinical insights into surgical decisions and post-op patient management.

 

Mr. Lurui Wang | Machine Learning | Best Researcher Award

Posted on by sciencefather

Mr. Lurui Wang | Machine Learning | Best Researcher Award

Mr. Lurui Wang, Univeristy of toronto Mind lab, Canada.

Lurui Wang is a passionate and innovative researcher in the field of mechanical engineering, with a strong interdisciplinary interest in robotics, artificial intelligence, and sensor technologies. Currently pursuing his Bachelor of Science in Mechanical Engineering at the University of Toronto, he combines practical experience, academic excellence, and a drive for impactful innovation. With an impressive GPA of 3.75 and extensive involvement in machine learning and design projects, Lurui has contributed to multiple high-impact research areas such as cold spray coatings, aerosol systems for medical applications, and intelligent object detection models. His leadership skills are evident through various team-led design and AI projects, as well as his industry internship with Baylis Med Tech, where he made significant technical contributions.

Professional Profile

ORCID

🎓 Education Background

Lurui Wang began his academic journey at the University of Toronto in September 2020 and is expected to graduate in April 2025 with a Bachelor of Science in Mechanical Engineering. His curriculum includes key subjects such as Mechanical Engineering Design, Mechatronics, Fluid Mechanics, and Solid Mechanics, enhanced by the Professional Experience Year (PEY Co-op). He also undertook summer courses at Xiamen University in accounting, microeconomics, and macroeconomics, reflecting his interdisciplinary interests.

💼 Professional Experience

Lurui’s hands-on experience spans several high-impact projects and internships. He has been involved in developing deep learning models for acoustic emission sensor data in cold spray coatings, advanced object detection through SparseNetYOLOv8, and designing heater systems for aerosol deposition studies. Notably, at Baylis Med Tech, he served as an Equipment Engineer, leading the design of a cable coiling machine, improving manufacturing efficiency, and reducing operational costs. He has also led student design projects in robotics, AI traffic signal detection, and mechanical systems such as gearboxes and milling machines, showcasing his engineering versatility.

🏆 Awards and Honors

Lurui Wang’s dedication has been recognized through multiple accolades, including the Certified SolidWorks Professional (CSWP) in 2022 and Associate (CSWA) in 2021. In 2024, he earned a Kaggle Silver Medal in the “Eedi – Mining Misconceptions in Mathematics” competition, ranking among the top 67 out of 1,446 participants, underscoring his strong data science capabilities.

🔬 Research Focus

Lurui’s research focuses on the intersection of mechanical systems, intelligent computation, and biomimicry. His works explore robotic optimization using insect-inspired mechanisms, machine learning integration in engineering systems, sensor fusion for predictive manufacturing, and vision-based detection models using YOLO architecture enhancements. His projects aim to address real-world challenges in autonomous systems, medical technology, and intelligent manufacturing, driven by simulation tools, programming, and algorithmic innovation.

🔚 Conclusion

Lurui Wang stands out as a dynamic and driven early-career researcher, blending engineering design, data science, and real-world application with academic rigor. His proactive approach, technical skillset, and collaborative mindset mark him as a rising talent in the fields of intelligent mechanical systems and applied machine learning.

📚 Top Publications with Notes

  1. Design and Optimization of Monopod Robots for Continuous Vertical Jumping: A Novel Hopping Mechanism Inspired by Froghoppers and Grasshoppers

    • Authors: Suhang Xu, Feihan Li, Lurui Wang, Yujing Fu

    • Published Year: 2024

    • Journal: Proceedings of MLPRAE 2024

    • DOI: 10.1145/3696687.3696695

  2. SparseNetYOLOv8: Integrating Vision Transformers and Dynamic Probing for Enhanced Sparse Object Detection

    • Authors: Lurui Wang, Yanfeng Lyu

    • Published Year: 2024

    • Conference: 2024 International Conference on Computer Vision and Image Processing (CVIP 2024)

    • DOI: 10.1117/12.3058039

  3. A Machine Learning Approach for Predicting Particle Spatial, Velocity, and Temperature Distributions in Cold Spray Additive Manufacturing

    • Authors: Lurui Wang, Mehdi Jadidi, Ali Dolatabadi

    • Published Year: 2025

    • Conference: Applied Sciences

    • DOI: 10.3390/app15126418