Dr. Shengfei Ji | Mechanical | Best Researcher Award

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Dr. Shengfei Ji | Mechanical | Best Researcher Award

Dr. Shengfei Ji , China University of Mining and Technology, China

Shengfei Ji is a dedicated Ph.D. candidate in Mechatronic Engineering at the School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, P.R. China. With a strong academic and technical background, he focuses on developing intelligent systems to enhance the operational reliability of hydraulic machinery. His passion for research and innovation in fault diagnosis and predictive modeling has led to several impactful publications in renowned journals.

Publication Profile

Scopus

ORCID

🎓 Education Background

Shengfei Ji is currently pursuing his Ph.D. in Mechatronic Engineering at China University of Mining and Technology, where he is engaged in advanced studies on intelligent condition monitoring systems. His academic foundation includes rigorous training in machine learning, system dynamics, and hydraulic machinery.

💼 Professional Experience

As a Ph.D. researcher, Shengfei has collaborated with a multidisciplinary team on projects involving construction machinery and intelligent fault detection. His work involves both theoretical research and practical application, integrating AI technologies like graph convolutional networks and LSTM models with mechanical systems. He has co-authored research with industry and academic experts, further expanding his expertise in smart diagnostics.

🏆 Awards and Honors

While formal awards and grants are not currently listed, Shengfei Ji’s work has gained recognition in the academic community with citations in 19 documents and a Scopus h-index of 2, reflecting growing interest in his innovative contributions to intelligent machinery diagnostics.

🔬 Research Focus

Shengfei Ji’s core research interests lie in intelligent fault diagnosis 🛠️, anomaly detection 🚨, and condition monitoring 📡 of hydraulic systems used in construction machinery. His work primarily applies deep learning and graph-based methods to create predictive models that enhance machine efficiency and reliability.

📝 Conclusion

With a strong commitment to integrating AI with mechanical systems, Shengfei Ji is emerging as a promising researcher in the field of mechatronic engineering. His scientific contributions reflect a unique intersection of engineering insight and computational intelligence, positioning him for continued academic and industrial impact 🌐.

📚 Top Publications

  1. Multivariate Prediction Soft Sensor Model for Truck Cranes Based on Graph Convolutional Network and Random Forest
    Published in: Actuators, 2024

  2. A Soft Sensor Model for Predicting the Flow of a Hydraulic Pump Based on Graph Convolutional Network–Long Short-Term Memory
    Published in: Actuators, 2024

  3. Bucket Teeth Detection Based on Faster Region Convolutional Neural Network
    Published in: IEEE Access, 2021
    Cited by: 19 articles

 

Dr. Kristina P. Sinaga | Clustering | Best Researcher Award

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Dr. Kristina P. Sinaga | Clustering | Best Researcher Award

Dr. Kristina P. Sinaga, postdoc researcher, ISTI-CNR, Italy

👩‍🔬 Kristina P. Sinaga, Ph.D., is a passionate applied mathematician and postdoctoral researcher at ISTI-CNR, Italy, specializing in innovative clustering algorithms and federated learning for multi-view data analysis. She bridges theory and practice with elegant, robust AI solutions tailored for complex heterogeneous systems, with a keen interest in medical diagnostics and healthcare analytics. Kristina is also the creator of NeuralGlow.AI, a creative blog blending algorithmic thinking with personal insight.

Publication Profile

Summary of Suitability for Best Research Award – Dr. Kristina P. Sinaga

Dr. Kristina P. Sinaga is a distinguished applied mathematician whose pioneering research in multi-view clustering algorithms and federated learning addresses complex challenges in heterogeneous data analysis and privacy preservation. Her innovative contributions have advanced pattern recognition and dimensionality reduction techniques with promising applications in medical diagnostics and healthcare analytics. With a robust publication record and over 2,500 citations, Dr. Sinaga exemplifies research excellence through impactful, practical algorithms that bridge theory and real-world problems. Her leadership in international collaborations, dedication to mentorship, and commitment to STEM education further highlight her as an outstanding candidate for the Best Research Award.

Education Background

🎓 Kristina earned her Ph.D. in Applied Mathematics from Chung Yuan Christian University, Taiwan, graduating with honors in 2020. Her doctoral research focused on multi-view fuzzy clustering algorithms for heterogeneous data. She holds an M.Sc. in Mathematics from the University of Sumatera Utara, Indonesia, where she developed novel stochastic optimization models, and a B.Sc. in Mathematics from the same university, graduating with academic distinction.

Professional Experience

💼 Since October 2024, Kristina has been a Postdoctoral Researcher at ISTI-CNR, leading federated learning projects and developing clustering methods for complex datasets. Previously, she served as a Lecturer Specialist at Bina Nusantara University, Indonesia, teaching advanced mathematics and mentoring student research. Her academic journey also includes pioneering multi-view clustering research as a Ph.D. student in Taiwan and active community STEM outreach efforts.

Awards and Honors

🏆 Kristina’s academic career is marked by honors for her doctoral work and contributions to applied mathematics. While specific awards are not detailed, her multiple high-impact publications and strong citation record (over 2,500 citations) underscore her scholarly influence and research excellence.

Research Focus

🔬 Her research centers on advanced clustering algorithms (k-means, fuzzy c-means) tailored for multi-view data, dimensionality reduction techniques, pattern recognition, and privacy-preserving federated learning in multi-client environments. She excels in algorithmic optimization to enhance performance in unpredictable and heterogeneous data conditions.

Conclusion

✨ Kristina Sinaga embodies a rare blend of mathematical rigor and creative innovation. She thrives on challenging boundaries in AI and machine learning, producing research that is not only effective but intuitively elegant. Her dedication to teaching, research, and public engagement highlights a holistic approach to advancing science and education globally.

Publication Top Notes

  1. Multi-view fuzzy clustering algorithms for multi-view data. Applied Soft Computing.

    • Published Year: 2020

    • Journal: Applied Soft Computing

    • Citations: 800+

  2. Stochastic optimization model for ambulance location problems with correlation. European Journal of Operational Research.

    • Published Year: 2018

    • Journal: European Journal of Operational Research

    • Citations: 400+

  3.  Privacy-preserving federated multi-view clustering algorithms. IEEE Transactions on Neural Networks and Learning Systems.

    • Published Year: 2021

    • Journal: IEEE Transactions on Neural Networks and Learning Systems

    • Citations: 600+

  4. Dimensionality reduction techniques based on clustering for heterogeneous data systems. Information Sciences.

    • Published Year: 2023

    • Journal: Information Sciences

    • Citations: 300+

  5.  Federated learning with communication constraints for multi-view datasets. Pattern Recognition Letters.

    • Published Year: 2022

    • Journal: Pattern Recognition Letters

    • Citations: 200+

 

Dr . Yuhai Li | Interface treatment | Best Researcher Award

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Dr . Yuhai Li | Interface treatment | Best Researcher Award

Postdoctoral fellow, China Academy of Engineering Physics, China

Yuhai Li is a dedicated researcher specializing in optical engineering and mechanical engineering with a strong focus on laser-material interactions and plasma cleaning techniques. Currently, he is a postdoctoral researcher at the China Academy of Engineering Physics. With a robust academic foundation and multiple high-impact publications, Yuhai is contributing significantly to advancements in optical thin film cleaning and damage analysis. 🔬✨

Publication Profile

Summary of Suitability for Best Researcher Award – Dr. Yuhai Li

Dr. Yuhai Li has made significant contributions to high-intensity laser optics and plasma cleaning technologies, with a focus on material damage control and light-matter interactions. His prolific research, published in top-tier journals, demonstrates innovation, impact, and relevance, making him an outstanding candidate for the Best Researcher Award.

Education Background

Yuhai Li completed his doctoral and master’s degrees in Mechanical Engineering at Harbin Institute of Technology (2017-2023) and earned his bachelor’s degree in Mechanical Engineering from Northeast Agricultural University (2013-2017). Currently, he is pursuing postdoctoral research in Optical Engineering at the China Academy of Engineering Physics since September 2023. 🎓📚

Professional Experience

His professional experience revolves around experimental and simulation studies on surface cleaning of optical components, damage characteristics of laser optical films, and plasma treatment technologies. Yuhai has participated in projects related to large-aperture optics for inertial confinement fusion (ICF) and heritage conservation using plasma cleaning methods. 🛠️🔍

Awards and Honors

While specific awards are not listed, Yuhai’s work is recognized through publications in reputable journals and international conferences, indicating his active role and contribution in the scientific community. 🏅📈

Research Focus

Yuhai Li’s research centers on plasma cleaning of optical surfaces, interaction between laser and materials, contamination damage mechanisms, and molecular dynamics simulation of plasma effects. His work addresses practical challenges in high-power laser facilities and the preservation of cultural heritage through non-destructive cleaning techniques. ⚛️💡

Conclusion

With a blend of theoretical insight and experimental expertise, Yuhai Li is a promising scholar advancing the frontiers of optical materials science and laser engineering. His continuous contributions through research and publications underscore his commitment to innovation in optical engineering. 🚀📖

Publication Top Notes

  1. In situ plasma cleaning of large-aperture optical components in ICF, Nuclear Fusion, 2022, 62(7): 076023.
    Cited by many for advancements in plasma cleaning techniques for optical components in fusion technology.

  2. Long-lasting antifogging mechanism for large-aperture optical surface in low-pressure air plasma in-situ treated, Applied Surface Science, 2022, 581: 152358.
    Highly referenced work on antifogging plasma treatment of optical surfaces.

  3. The mechanism study of low-pressure air plasma cleaning on large-aperture optical surface unraveled by experiment and reactive molecular dynamics simulation, Plasma Science and Technology, 2022, 24(6): 064012.
    Provides molecular-level insights into plasma cleaning, cited for simulation and experimental synergy.

  4. Time-resolved imaging for investigating laser-material interactions during laser irradiation cleaning on murals, Optics & Laser Technology, 2023, 157: 108679.
    Noted for innovative application of laser cleaning in cultural heritage.

  5. In-situ measurement and self-calibration system for high-power laser energy in ICF facilities, Optics & Laser Technology, 2024, 170: 110108.
    Important contribution to precision measurement in laser fusion facilities.

 

Shang-Kuan Chen | Deep Reinforcement Learning | Excellence in Research Award

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Assist. Prof. Dr. Shang-Kuan Chen | Deep Reinforcement Learning | Excellence in Research Award

Assistant Professor, YZU university Taiwan

Shang-Kuan Chen is a dedicated researcher and academician specializing in computer science, with a robust focus on data hiding, visual cryptography, image sharing, and image retrieval. He received his MS in Applied Mathematics in 1998 and a PhD in Computer Science in 2006 from National Chiao Tung University, Taiwan. Currently serving as an Assistant Professor at the Department of Computer Science and Engineering, Yuan Ze University (since 2023), Dr. Chen is known for blending theoretical insights with practical applications in cybersecurity and intelligent systems. Over the years, he has contributed significantly to high-impact research, publishing extensively in SCI-indexed journals and international conferences. His innovative work on QR code systems, smart infrastructures, and optimization algorithms reflects his interdisciplinary expertise. In addition to his academic contributions, Dr. Chen actively mentors students and engages in collaborative research projects.

Publication Profile

Summary of Suitability for Excellence in Researcher Award – Assist. Prof. Dr. Shang-Kuan Chen

Assist. Prof. Dr. Shang-Kuan Chen is a prolific researcher with impactful contributions in data hiding, visual cryptography, and image sharing. His SCI-indexed publications reflect innovation, interdisciplinary application, and academic rigor. With a commitment to advancing secure image technologies, he exemplifies excellence and originality deserving of the Best Researcher Award.

🎓 Education

Shang-Kuan Chen began his academic journey with a Master of Science degree in Applied Mathematics from National Chiao Tung University, Taiwan, in 1998. Motivated by a passion for algorithms, mathematical models, and computer science, he further pursued and completed a PhD in Computer Science from the same university in 2006. His doctoral studies equipped him with in-depth knowledge in information security, image processing, and computational intelligence. The foundation of applied mathematics laid the groundwork for his advanced research in visual cryptography and optimization methods. His interdisciplinary education has allowed him to merge theoretical mathematical principles with practical computer science solutions. Throughout his educational path, Dr. Chen demonstrated academic excellence and a commitment to solving real-world problems through algorithmic thinking and cryptographic innovation, which continues to inform his research and teaching.

💼 Experience

Dr. Shang-Kuan Chen currently serves as an Assistant Professor in the Department of Computer Science and Engineering at Yuan Ze University, Taiwan, since 2023. With nearly two decades of academic and research experience, Dr. Chen has held various positions in both teaching and research capacities, contributing to topics such as data hiding, visual cryptography, and secure image sharing. His extensive publication record—spanning from 2005 to 2025—shows consistent involvement in SCI and EI-indexed journals and projects involving applied image processing and optimization techniques. Dr. Chen has also contributed to collaborative research efforts involving smart systems and cybersecurity frameworks. His work is often interdisciplinary, bridging areas like embedded systems, mobile information processing, and AI-powered visual technologies. At Yuan Ze University, he not only teaches but also supervises research students, pushing boundaries in secure digital communication and computational image processing.

🏆 Awards & Honors 

While specific awards are not explicitly listed, Shang-Kuan Chen’s prolific publication record in prestigious SCI-indexed journals such as Pattern Recognition, Optical Engineering, Symmetry, and Electronics stands as a testament to his scholarly excellence. His works have been recognized in high-impact areas like secure QR code systems, visual secret sharing, and differential evolution algorithms—topics critical to the future of information security and optimization. Publications with impact factors as high as 7.196 (Pattern Recognition) and multiple collaborative projects suggest his research is both influential and widely cited. His role as lead or co-author in numerous interdisciplinary papers and ongoing contributions in electronics and AI research highlight his continuous impact. Furthermore, his consistent scholarly output over nearly two decades, with multiple publications every year, reflects peer recognition and academic respect in the fields of computer vision, applied cryptography, and smart computing systems.

🔬 Research Focus 

Shang-Kuan Chen’s research centers around data hiding, visual cryptography, image sharing, QR code systems, and optimization algorithms. He explores advanced methods to securely encode and share visual data, particularly in healthcare, smart infrastructure, and mobile environments. His work on multi-layered QR-code systems enables secure medication administration, while visual secret sharing techniques aim to enhance data privacy and integrity. More recently, Dr. Chen has delved into deep learning and differential evolution algorithms, as reflected in his 2025 publications, to solve complex optimization problems and enable robust AI-driven fingerprint recognition systems. His work bridges the gap between theoretical cryptography and practical systems implementation, targeting real-world applications like smart refrigerators, nuclear scheduling, and autonomous decision-making. Dr. Chen continues to investigate how intelligent algorithms can reinforce secure communication and visual processing, positioning him as a leading contributor to secure AI-based systems and visual information technology.

 Conclusion

Dr. Shang-Kuan Chen is a strong candidate for the Excellence in Research Award, given his sustained scholarly output, innovative methodologies, and contributions to image processing, cryptography, and optimization. His ability to evolve with technological advances and publish in recognized journals underlines his merit for recognition. With strategic focus on broader collaboration and outreach, Dr. Chen is poised to make even greater strides in scientific excellence.

📚 Top Publications with Details

  • Memory-Based Differential Evolution Algorithms with Self-Adaptive Parameters for Optimization Problems • 2025 • Shang-Kuan Chen, Gen-Han Wu, Yu-Hsuan Wu • https://doi.org/10.3390/math13101647

  • A Hybrid Deep Learning and Feature Descriptor Approach for Partial Fingerprint Recognition • 2025 • Zhi-Sheng Chen, Chrisantonius, Farchan Hakim Raswa, Shang-Kuan Chen, Chung-I Huang, Kuo-Chen Li, Shih-Lun Chen, Yung-Hui Li, Jia-Ching Wang • https://doi.org/10.3390/electronics14091807

  • Memory-Based Differential Evolution Algorithms with Self-Adaptive Parameters for Optimization Problems (working paper) • 2025 • Shang-Kuan Chen, Gen-Han Wu, Yu-Hsuan Wu • https://doi.org/10.20944/preprints202504.0563.v1

 

Prof. Tao Ye | AI Accelerator | Best Researcher Award

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Prof. Tao Ye | AI Accelerator | Best Researcher Award

Prof, The Chinese University of Hong Kong, China

Dr. Terry Tao Ye is a renowned professor and researcher specializing in electrical and electronic engineering, nanotechnology, and smart sensing systems. Currently affiliated with the School of Science and Engineering at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), he has made significant contributions to the fields of RFID systems, embedded platforms, and wearable electronics. With a rich career spanning academia and industry, Dr. Ye has played pivotal roles in developing foundational technologies and fostering cutting-edge research in China and internationally. 🌏🔬

Publication Profile

Summary of Suitability for Best Researcher Award – Prof. Tao Ye

Dr. Terry Tao Ye is a prolific researcher and leader with groundbreaking contributions in nanoscience, wearable sensors, and SoC design. His extensive high-impact publications, prestigious grants, and interdisciplinary innovations demonstrate exceptional research excellence and influence, making him highly deserving of the Best Researcher Award.

🎓 Education Background

Dr. Ye holds a Ph.D. in Electrical Engineering from Stanford University, California, USA (1995–2004), where he researched Systems-on-Chip and Embedded Systems under the guidance of Dr. Giovanni De Micheli. He earned his B.Eng. from the Department of Electronic Engineering at Tsinghua University, Beijing, China (1988–1993), solidifying a strong foundation in electronics and communication engineering. 📘🎓

💼 Professional Experience

Dr. Ye has held multiple esteemed academic and industrial positions. He is currently a Professor at CUHK-Shenzhen (2025–present) and also at SUSTech (2018–present). He holds an adjunct professorship at Carnegie Mellon University since 2015 and has served in leadership and professorial roles at Sun Yat-Sen University and the Joint Institute of Engineering with CMU. His industry experience includes significant roles at Impinj Inc. in Seattle, where he led the development of RFID Gen2 standards, and Synopsys Inc., where he pioneered ASIC and EDA tools. His early career also includes roles at the Hong Kong LSCM R&D Center and Silicon Architects, contributing to foundational IC design technologies. 🧑‍🏫💻📡

🏅 Awards and Honors

Dr. Ye has secured over 30 competitive research grants as principal investigator or core member, spanning national, provincial, and institutional levels. Notably, his work has been funded by the National Science Foundation of China (NSFC), the Guangdong Provincial Key-Area R&D Program, and Shenzhen Science and Technology Program. His contributions to RFID, smart sensing, and embedded design have earned him widespread recognition in academia and industry. 🏆📑

🔬 Research Focus

Dr. Ye’s research interests include System-on-Chip design, embedded systems, energy-efficient interconnects, wearable electronics, flexible sensors, and e-textiles. He is currently leading projects on electronic skin, wireless medical devices, and high-frequency signal integrity in textile-based circuits. His interdisciplinary work bridges hardware design, signal processing, and biomedical applications. 🧠⚙️📲

🔚 Conclusion

With an outstanding blend of academic excellence and industrial innovation, Dr. Terry Tao Ye stands as a thought leader in electrical engineering and emerging smart technologies. His contributions to research, education, and global collaboration continue to shape the future of intelligent systems and nanotechnology. 🌟📡🔋

📚 Top Publications with Details

RV-SCNN: A RISC-V Processor With Customized Instruction Set for SNN and CNN Inference Acceleration on Edge Platforms, IEEE TCAD, 2025

Cited by: 12

Optimizing CNN Computation Using RISC-V Custom Instruction Sets for Edge Platforms, IEEE Transactions on Computers, 2024

Cited by: 2

Smartphone administered pulsed radio frequency energy therapy for expedited cutaneous wound healing, npj Digital Medicine, 2025

Cited by: 51
Polyelectrolyte-based wireless and drift-free iontronic sensors for orthodontic sensing, Science Advances, 2025

Cited by: 4

Parasitic Capacitance Modeling and Measurements of Conductive Yarns for e-Textile Devices, Nature Communications, 2023

Cited by: 8

Exploring RFID Technology for Wireless Control of Smart Antennas”, IEEE Internet of Things Journal, 2024

Cited by: 24

e-Bandage: Exploiting Smartphone as a Therapeutic Device for Cutaneous Wound Treatment”, Advanced Intelligent Systems, 2024

Cited by: 39

Ms. Yasmine Gaaloul | Photovoltaic systems | Best Researcher Award

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Ms. Yasmine Gaaloul | Photovoltaic systems | Best Researcher Award

PhD student, Higher School of Science and Technology Hammem Sousse, Tunisia

Yasmine Gaaloul is a passionate and innovative Ph.D. student in Physical Engineering, specializing in Energy, based in Sahloul, Sousse, Tunisia. With a sharp focus on advanced energy systems and renewable energy technologies, she brings a solid academic foundation combined with hands-on experience in photovoltaic system diagnostics and energy efficiency. Her academic journey reflects a strong dedication to contributing meaningful solutions in the field of sustainable energy using cutting-edge artificial intelligence techniques. 🌱⚡

Publication Profile

Scopus

Summary of Suitability for Best Researcher Award – Ms. Yasmine Gaaloul

Yasmine Gaaloul is a dedicated and innovative PhD student with a strong specialization in renewable energy systems, particularly in fault diagnosis of photovoltaic (PV) systems in DC microgrids using artificial intelligence (AI). Her research is highly relevant to current global challenges in energy sustainability and smart grid technology.

🎓 Education Background

Yasmine pursued her Bachelor’s Degree in Physics (2017–2020) and then earned a Research Master’s Degree in Physics with an Energy Track from Hammem Sousse Higher School of Science and Technology (2020–2022). She is currently enrolled in a Ph.D. program in Physical Engineering at the same institution, where her research focuses on fault diagnosis in photovoltaic (PV) systems using AI tools. Her academic path shows consistent advancement in renewable energy domains. 🎓🔬📚

💼 Professional Experience

Yasmine has built practical experience through internships and projects focused on energy audits, policy compliance, project management, and the design and implementation of energy systems. Notably, she undertook an application internship in Nuclear Medicine at the Tunisian Hospital-University Center in Sousse. She also possesses strong technical skills in simulation and programming tools such as MATLAB, PVsyst, and BAO EVOLUTION, which enhance her applied research capabilities. 🏥💻🔧

🏆 Awards and Honors

While no formal awards are listed, her work speaks volumes through peer-reviewed publications and technical skills in diagnosing photovoltaic faults using AI — a field of growing significance. Her continued progress and engagement in advanced renewable technologies position her as a competitive researcher with promising prospects. 🥇📈

🔬 Research Focus

Yasmine’s core research revolves around the fault detection and diagnosis of PV systems in DC microgrids using artificial intelligence. She also works on simulation and modeling of energy systems, including photovoltaic modules and converters. Her use of machine learning algorithms like Random Forest and KNN for predictive maintenance of PV systems reflects a modern and sustainable approach to energy reliability and performance optimization. Her work aligns with critical global goals for clean and efficient energy. ⚙️🔋🌞

✅ Conclusion 

Given her specialized research in photovoltaic systems and renewable energy using artificial intelligence, Yasmine Gaaloul is a strong candidate for the Research for Best Researcher Award. Her interdisciplinary approach, combining physical engineering with AI, positions her at the forefront of sustainable energy innovation. Her academic trajectory, technical prowess, and publication record demonstrate exceptional promise and dedication. 🏅🌍💡

📚 Top Publications with Notes

Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models (2023)

This study explores hybrid AI techniques to enhance PV system monitoring. Cited by: X articles

Comparative Performance Analysis of Metaheuristic Optimization Algorithms for Parameter Identification of Photovoltaic Cell/Module (2023)

This comparative work evaluates algorithms for optimal PV module performance. Cited by: X articles

Modeling and Simulation of a Two-Phase Interleaved Boost Converter for Photovoltaic Applications (2022)

Focuses on the design of efficient converters for PV systems. Cited by: X articles

Thittaporn Ganokratanaa | Computer Vision | Best Researcher Award

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Assist. Prof. Dr. Thittaporn Ganokratanaa | Computer Vision | Best Researcher Award

Lecturer at King Mongkut’s University of Technology Thonburi, Thailand

Dr. Thittaporn Ganokratanaa is an Assistant Professor in the Applied Computer Science Programme at King Mongkut’s University of Technology Thonburi. She is a dynamic academic leader involved in national and international committees including IEEE and AIAT. She actively advises innovation projects and engages in AI policy shaping in Thailand. With a strong academic and research background, she contributes significantly to the fields of artificial intelligence and multimedia signal processing. Dr. Thittaporn is widely recognized for her innovative spirit, mentorship, and leadership in applied research and education.

Publication Profile🌏📚

Academic Background🎓

Dr. Thittaporn holds a Ph.D. in Electrical Engineering with a focus on Multimedia and Signal Processing from Chulalongkorn University, with research collaboration at the University of Trento, Italy. She earned her M.Eng. from Chulalongkorn University with a GPA of 3.92 and her B.Sc. in Media Technology with first-class honors and a gold medal from KMUTT. Her academic journey is marked by multiple prestigious scholarships and fellowships, reflecting her academic excellence and commitment to research in AI, signal processing, and biomedical technology.

Professional Experience📊

Dr. Thittaporn currently serves as an Assistant Professor at KMUTT and holds several key leadership roles including Secretary of the IEEE Thailand Section and committee positions in IEEE MGA, CQC, and AIAT. She has contributed to national AI advisory committees and has served as advisor to several award-winning student innovation projects. Her career is defined by interdisciplinary collaboration, global engagement, and dedication to advancing computer science and AI education. She actively participates in conferences, policy development, and technical review roles in the academic and governmental sectors.

Awards and Honors🏆🥇

Dr. Thittaporn has received numerous prestigious awards, including the Grand Prize and Gold Medal at JDIE2024, multiple National Research Council of Thailand innovation awards, and Best Presentation at CSoNet 2024. She has been awarded both nationally and internationally for her innovative projects such as robotic prosthetics and AI-driven healthcare solutions. Her mentorship has led to student accolades at events like NSC and CommTECH. Recognized by organizations like UNOOSA and NUS, her work continues to drive excellence in AI research and technological innovation

Research Focus🔬

Dr. Thittaporn’s research interests span artificial intelligence, video anomaly detection, computer vision, human-computer interaction, multimedia signal processing, and the Internet of Things. She focuses on applying machine learning to solve real-world problems in healthcare, education, and smart technologies. Her projects include intelligent assistive devices, AI-powered learning platforms, and robotic systems. She integrates innovation with societal impact, aiming to bridge research and practical applications. Her interdisciplinary approach and global collaborations support her goal of creating technology that is ethical, inclusive, and transformative.

Publication Top Notes📊

Unsupervised anomaly detection and localization based on deep spatiotemporal translation network
citation: 123
year: 2020

Video anomaly detection using deep residual-spatiotemporal translation network
citation: 39
year: 2022

Iot system design for agro-tourism
citation: 33
year: 2021

Development of a process to enhance the reimbursement efficiency with OCR and ontology for financial documents
citation: 32
year: 2022

Voice-activated assistance for the elderly: Integrating speech recognition and IoT
citation: 20
year: 2024

Sorting red and green chilies by digital image processing
citation: 19
year: 2023

Smart agricultural greenhouses for earthworm farming
citation: 19
year: 2023

Pillow for detecting snoring with embedded techniques for elderly people with snoring problems
citation: 16
year: 2023

Real-Time Credit Card Fraud Detection Surveillance System
citation: 16
year: 2023

Conclusion🌏

Dr. Thittaporn Ganokratanaa is an outstanding candidate for the Best Researcher Award, with a strong track record in artificial intelligence, computer vision, multimedia signal processing, and human-computer interaction. Her academic excellence—evident from her Ph.D. in Electrical Engineering with international collaboration and multiple scholarships—pairs seamlessly with her innovation-driven research, reflected in numerous national and international awards, including from NRCT and JDIE. She actively contributes to impactful real-world applications, such as AI-assisted healthcare technologies and smart systems. Her leadership roles in IEEE Thailand, the AI Association of Thailand, and advisory committees for national AI policy underscore her influence in both academia and policy. Additionally, her mentorship of award-winning student projects highlights her dedication to shaping future researchers. Overall, Dr. Thittaporn exemplifies the qualities of a top-tier researcher with global impact, national relevance, and visionary leadership.

 

 

MARIA KANTZANOU | Medical | Best Researcher Award

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Assoc. Prof. Dr. MARIA KANTZANOU | Medical | Best Researcher Award

Assoc. Prof of Medical Microbiology & Parasitology, Medical School, National and Kapodistrian University of Athens, Greece

Dr. Maria Kantzanou is a distinguished Medical Biopathologist and Associate Professor of Medical Microbiology at the National and Kapodistrian University of Athens, Greece. With a robust background in clinical microbiology and molecular diagnostics, she has significantly contributed to infectious disease research and epidemiology. Known for her leadership roles in national reference centers and academic excellence, Dr. Kantzanou combines clinical practice, teaching, and research to advance public health. 🌟

Publication Profile

🎓 Education Background

Dr. Kantzanou holds a Medical Degree from the National Kapodistrian University of Athens and earned her PhD with excellent honors from the same institution. She specialized in Medical Biopathology (Microbiology) and Public Health-Social Medicine. Additionally, she completed a Master of Science in Health Unit Management at the Hellenic Open University. Her postgraduate experience includes clinical and research fellowship at the University of Oxford, UK. 🎓📜

💼 Professional Experience

Her extensive career spans university hospitals, national reference centers, and private diagnostic laboratories. Highlights include her tenure as Clinical Assistant at Oxford, Consultant at Larissa University Hospital, and Director of the National Retrovirus Reference Center in Athens. Since 2022, she serves as the Responsible Physician-Biopathologist at Eugenidion Hospital. Alongside academic roles, she holds key administrative positions in public health organizations and scientific societies. 🏥🔬

🏅 Awards and Honors

Dr. Kantzanou’s work has earned her national recognition for excellence in research and leadership in infectious disease control. She has been entrusted with numerous administrative responsibilities, including board memberships of Greek health organizations and presidency of the Hellenic Association of Medical Law. Her scientific impact is reflected in a high h-index and numerous invitations as a speaker and coordinator in scientific conferences. 🏆🎖️

🔬 Research Focus

Her research centers on molecular microbiology, epidemiology, and infection prevention. Dr. Kantzanou has specialized in diagnostic molecular techniques such as PCR and RT-PCR for bacterial and viral infections. Her work at the National Retrovirus Reference Center emphasizes HIV/AIDS diagnostics and research. Recent publications cover surgical site infections, viral detection in HIV patients, and infection control in clinical settings. 🧬🦠

✍️ Conclusion

Dr. Maria Kantzanou is a leading figure in medical microbiology, whose academic, clinical, and research contributions profoundly impact infectious disease management and healthcare epidemiology in Greece. Her dedication to teaching and mentoring alongside active participation in healthcare administration showcases her multifaceted expertise and commitment to advancing medical science and public health. 🌍💡

📚 Publication Top Notes

Prevalence of Osteosynthesis Hardware Removal Due to Surgical Site Infections Following Sagittal Split Osteotomy: A Systematic Review and Meta-Analysis
Journal of Clinical Medicine (2025)
DOI: 10.3390/jcm14103558
Cited by multiple articles exploring surgical infection control and maxillofacial surgery outcomes.

Prevalence of HHV-6 Detection Among People Living with HIV: A Systematic Review and Meta-Analysis
Viruses (2025)
DOI: 10.3390/v17040531
Cited extensively in virology and HIV co-infection research.

Prevalence of Surgical Site Infections Following Coronectomy: A Systematic Review and Meta-Analysis
Dentistry Journal (2024)
DOI: 10.3390/dj12120379
Widely referenced in dental surgery and infection prevention studies.

Prevalence of Leishmaniasis among Blood Donors: A Systematic Review and Meta-Analysis
Diseases (2024)
DOI: 10.3390/diseases12070160
Important reference in tropical disease and transfusion medicine research.

Prevalence of surgical site infections following extraction of impacted mandibular third molars: A systematic review and meta-analysis
Journal of Stomatology, Oral and Maxillofacial Surgery (2024)
DOI: 10.1016/j.jormas.2024.101995
PMID: 39084557
Cited in oral surgery and clinical epidemiology literature.

The Existence-Relatedness-Growth Theory for Job Satisfaction and Motivation of Greek National Healthcare Service Employees in the Context of Severe Financial Constraints
Cureus (2024)
DOI: 10.7759/cureus.62738
PMID: 39036167
Relevant in healthcare workforce motivation and management studies.

Prevalence of free flap failure in mandibular osteoradionecrosis reconstruction: a systematic review and meta-analysis
Scientific Reports (2024)
DOI: 10.1038/s41598-024-61862-1
Highly cited in reconstructive surgery and oncology-related infection research.

 

 

Tun Zhao | Integration | Best Academic Researcher Award

Published on by Computer Scientists Awards

Dr. Tun Zhao | Integration | Best Academic Researcher Award

Lecturer at  Yan’an university, China

Dr. Tun Zhao is a dedicated scholar specializing in Buddhist literature, version bibliography, East Asian Han literature, and Buddhist history. Currently serving as an editorial board member of Education and Research and a reviewer for the Southern Journal, he holds the title of “Eagle Scholar” at the Hubei Yangtze River Culture Research Institute. Affiliated with Yan’an University, Dr. Zhao has made significant contributions to the study of Yuan Dynasty Buddhist Canon scriptures, offering insights into their publication, regional printing patterns, and the roles of secular and royal entities in their dissemination. He has published eight journal articles indexed in A&HCI, Scopus, and CSSCI, alongside a scholarly book. His research has received institutional support through grants, such as his project on the Puning Canon preserved in Japan. Through a combination of rigorous historical analysis and commitment to textual scholarship, Dr. Zhao is advancing the academic understanding of East Asian religious and cultural heritage.

Publication Profile

Education 🎓 

Dr. Tun Zhao has pursued an academic path deeply rooted in the study of Chinese Buddhist literature and historical texts. He earned his doctoral degree with a dissertation titled Research on the Publication of Chinese Buddhist Scriptures in the Yuan Dynasty in 2023, demonstrating a strong foundation in textual analysis, historical bibliography, and cultural history. His education has been marked by a commitment to exploring the intersections of literature, religion, and history, with a particular emphasis on the evolution and dissemination of Buddhist canonical texts. Dr. Zhao’s academic training has equipped him with expertise in paleography, classical Chinese, and East Asian cultural studies, enabling him to engage critically with historical documents and rare scriptural editions. His scholarly development has also been supported by institutional grants and active participation in academic societies related to historical literature and poetry. This rigorous educational background underpins his ongoing contributions to the humanities and Buddhist textual scholarship.

Professional Experience 💼 

Dr. Tun Zhao has cultivated a robust professional profile in the fields of Buddhist literature and historical research. He currently serves as an editorial board member of Education and Research (Singapore Arts and Sciences Press) and acts as a peer reviewer for the Southern Journal, reflecting his active engagement in academic publishing and scholarly evaluation. Recognized as an “Eagle Scholar” by the Hubei Yangtze River Culture Research Institute, he is affiliated with Yan’an University, where he contributes to research and mentorship in the humanities. Dr. Zhao has led and participated in several research projects, including the prestigious Yan’an University Doctoral Research Initiation Grant for his study on the Puning Canon at Zojoji Temple in Japan. His professional work bridges historical scholarship and contemporary research needs, with eight peer-reviewed journal publications and a monograph to his credit. He also collaborates with religious and academic institutions, strengthening his role as a respected figure in East Asian literary studies.

Research Interest 🔬

Dr. Tun Zhao’s research interests center on Buddhist literature, version bibliography, East Asian Han literature, and the cultural and historical development of Buddhism, particularly during the Yuan Dynasty. He is deeply invested in studying the publication, transmission, and textual variations of Buddhist scriptures, with a focus on block-printed Canons. His work explores the diachronic evolution of Buddhist texts, emphasizing the socio-political and cultural influences that shaped their production and dissemination. Dr. Zhao is particularly interested in the spatial and typographic characteristics of Yuan Dynasty scripture editions, as well as the contributions of monastic, royal, and secular figures to the engraving of Buddhist texts. His interdisciplinary approach integrates literary analysis, cultural history, and bibliographic study, aiming to clarify the broader historical context of East Asian religious texts. Future research directions include comparative studies of Canon versions and further exploration of transnational Buddhist textual traditions, particularly between China and Japan.

Research Skill🔎

Dr. Tun Zhao possesses a comprehensive set of research skills that support his scholarly work in Buddhist literature and historical bibliography. He demonstrates advanced proficiency in classical Chinese textual analysis, enabling him to interpret ancient manuscripts and identify variations across scriptural editions. His expertise in version bibliography allows him to trace the publication history and transmission of Buddhist texts, particularly during the Yuan Dynasty. Dr. Zhao is skilled in comparative textual studies, typographic analysis, and cultural historiography, which he applies to uncover regional patterns in scripture production and the roles of different societal groups in the engraving process. He is adept at archival research, drawing from both Chinese and Japanese sources, and has experience securing and managing funded research projects. His academic writing and peer-reviewed publications reflect strong analytical and interpretive capabilities, while his editorial and reviewing roles demonstrate a refined understanding of scholarly standards and methodologies in the humanities.

Award and Honor🏆

Dr. Tun Zhao has been recognized for his academic excellence and scholarly promise through several awards and honors. Notably, he holds the title of “Eagle Scholar” at the Hubei Yangtze River Culture Research Institute, a distinction awarded to emerging scholars with significant contributions to cultural and historical research. He has also received the prestigious Doctoral Research Initiation Grant from Yan’an University for his project on the Puning Canon preserved at Zojoji Temple in Japan, highlighting institutional confidence in his research capabilities. In addition to these honors, Dr. Zhao has earned editorial appointments with respected academic journals, including serving as a board member of Education and Research and a reviewer for the Southern Journal, further reflecting his standing in the academic community. His scholarly publications in indexed journals and collaboration with religious institutions underscore his growing influence in the fields of Buddhist studies and East Asian historical literature.

Conclusion📝

Zhao Tun is highly suitable for the Best Research Scholar Award in the Humanities and Arts category. His research is original, culturally significant, and contributes meaningfully to the academic discourse on Buddhist texts and East Asian historical literature. Strengthened by publication in recognized journals, editorial involvement, and scholarly grant support, Zhao Tun exemplifies the qualities of a dedicated and impactful researcher. Enhancing visibility in international academic circles and exploring digital scholarship could further elevate his profile.

Recommendation: Strongly recommended for the Best Academic Researcher Award – Research Scholar (Humanities and Arts).

Publications Top Noted📚

 

Laura Umfleet | Health Sciences | Best Researcher Award

Published on by Computer Scientists Awards

Dr. Laura Umfleet | Health Sciences | Best Researcher Award

Associate Professor at Medical College of Wisconsin, United States

Dr. Laura Glass Umfleet, Psy.D., ABPP (CN), is an accomplished clinical neuropsychologist and Associate Professor of Neurology at the Medical College of Wisconsin. With expertise in adult cognitive disorders, especially neurodegeneration and congenital conditions, she is nationally certified by the American Board of Professional Psychology. Dr. Glass Umfleet serves as an editorial board member and an international leader in data-sharing initiatives. Her contributions span clinical practice, academic mentorship, and scientific collaboration, reinforcing her commitment to advancing neuropsychology through research, education, and open science initiatives. 🌍🧠📚

Publication Profile

Scopus

Academic background

Dr. Glass Umfleet earned her B.S. in Psychology with a Biology minor in 2006 and an M.S. in Psychology in 2008 from the University of Central Missouri. She completed her Psy.D. in Clinical Psychology from Roosevelt University, Chicago, in 2012 with APA accreditation. Her predoctoral internship at the University of Florida focused on neuropsychology, followed by a postdoctoral fellowship in Clinical Neuropsychology at the Medical College of Wisconsin and the Clement J. Zablocki VA Medical Center. Her educational journey reflects a strong foundation in clinical and cognitive neuroscience. 🎓📖🧬

Professional Experience

Since 2014, Dr. Glass Umfleet has served at the Medical College of Wisconsin as a Clinical Neuropsychologist, advancing to Associate Professor in 2021. She is also an Adjunct Assistant Professor at the University of Wisconsin-Milwaukee. Her clinical, academic, and leadership roles reflect her deep involvement in patient care, teaching, and research. Her professional path includes national and international presentations, peer-reviewed workshops, and active roles in neuropsychology organizations, positioning her as a respected expert in her field. 🏥📊👩‍🏫

Awards and Honors

Dr. Glass Umfleet’s professional recognition includes board certification in Clinical Neuropsychology by ABPP and editorial positions, such as Associate Editor for the Journal of Alzheimer’s Disease. She has been selected for numerous leadership roles in international neuropsychology societies, including chairing the INS WINDS SIG and serving on committees focused on student mentorship and open science. Her involvement in editorial reviews and scientific programs reflects high standing and trust in her scholarly expertise. 🏅🧠🌟

Research Focus

Dr. Glass Umfleet’s research focuses on cognitive functioning in aging and neurological conditions, including Alzheimer’s disease and adult congenital heart disease. She explores digital neuropsychological assessment, cognitive subtypes, and psychometric methods through collaborative networks like the National Neuropsychology Network. As Chair of INS WINDS, she champions data sharing and precision neuropsychology. Her work bridges clinical insight and innovative methodologies, promoting open science and advancing the field’s understanding of brain-behavior relationships. 🧪🧩💻

Publication Top Notes

🧠 Changes in cerebrovascular reactivity within functional networks in older adults with long-COVID

Year: 2025 | 🧬🧓🦠🧠 Frontiers in Neurology

🧪 Computerized adaptive test strategies for the matrix reasoning subtest of the Wechsler Adult Intelligence Scale, 4th Edition (WAIS-IV)

Year: 2024 | Cited by: 1 | 📊🧠📈📘 Journal of the International Neuropsychological Society

Conclusion

Dr. Laura Glass Umfleet is an exemplary clinical neuropsychologist whose sustained research productivity, innovative methodologies, and impactful publications over nearly two decades underscore her status as a leading figure in the field. Her national and international influence is evident through her leadership roles in global initiatives like the WINDS SIG and ACHD/Neuro Working Group, as well as frequent invited presentations at top-tier conferences. Board-certified by the ABPP and serving as Associate Professor at the Medical College of Wisconsin, Dr. Umfleet pairs academic excellence with clinical relevance. Her dedication to mentoring, editorial service, and advancing open science in neuropsychology further cements her as a highly deserving recipient of a Best Researcher Award.