Mr. André Guimarães | Computer Science | Best Researcher Award

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Mr. André Guimarães | Computer Science | Best Researcher Award

Researcher, University of Beira Interior, Portugal

Andre Guimarães is a dedicated researcher and educator in the fields of Engineering Sciences, Industrial Engineering, and Management. With a strong academic background, he has contributed significantly to various research projects related to Industry 4.0 and digital transformation. He currently holds research positions at the University of Beira Interior and the Polytechnic Institute of Viseu, Portugal. Alongside his academic work, Andre has accumulated practical experience in industrial environments, particularly in production management and technical consulting, where he focuses on quality management, lean methodologies, and engineering innovations. He is also a passionate educator, teaching engineering and management-related courses at the higher education level. 📚🔬

Publication Profile

ORCID

Education:

Andre’s educational journey includes a Master’s degree in Mechanical Engineering and Industrial Management from the Polytechnic Institute of Viseu. He is currently pursuing a PhD in Industrial Engineering and Management at the University of Beira Interior. Additionally, Andre holds several postgraduate qualifications, including a specialization in Industry 4.0 and Digital Transformation from the Polytechnic Institute of Porto. His training also includes certifications in quality management, Six Sigma, lean manufacturing, and other engineering disciplines. 🎓📖

Experience:

Andre’s professional career spans both academia and industry. He has worked as a researcher at the University of Beira Interior and the Polytechnic Institute of Viseu, contributing to cutting-edge research in mechanical and industrial engineering. Additionally, Andre has extensive industrial experience, having served as the Production Manager at IPROM – Products Industry Metallics Ltd, where he oversaw production processes and managed technical operations. As a consultant and facilitator at the Welding and Quality Institute, Andre applies his expertise in quality management systems and continuous improvement. 🏭⚙️

Awards and Honors:

Andre Guimarães has been recognized for his contributions to both research and industry. He is a full member of the Order of Engineers in Portugal and a fellow at FCT Research. His work has been acknowledged through various academic and industry accolades, cementing his reputation as a skilled professional and educator in his field. 🏅🌟

Research Focus:

Andre’s research interests are deeply rooted in Industry 4.0 technologies, digital transformation, lean management, and quality systems in industrial engineering. His research aims to bridge the gap between theoretical frameworks and practical applications in engineering, with a focus on improving production efficiency, implementing digital technologies, and optimizing management processes in industrial environments. His recent projects explore advanced methodologies in electromechatronics and systems research. 🔍📊

Conclusion:

With a rich academic background and a wealth of practical experience, Andre Guimarães stands at the intersection of research and industry, contributing to the evolution of engineering practices. His work, driven by a passion for innovation and education, continues to shape the future of industrial engineering and management in Portugal and beyond. Andre’s ongoing commitment to advancing the field through both research and practical applications makes him a valuable asset to the academic and industrial communities. 🚀🌍

Publications:

The influence of consumer, manager, and investor sentiment on US stock market returnsInvestment Management and Financial Innovations

Effects of Lean Tools and Industry 4.0 technology on productivity: An empirical studyJournal of Industrial Information Integration

Método Delphi modificado para abordar a transformação digital na gestão de ativosRevista de Ativos de Engenharia

Lean philosophy and Value Engineering methodologies. Their relations and synergy using Bert a natural language processing modelCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Modificação do Método Delphi para Aplicação num Questionário sobre a Transformação Digital na Gestão de AtivosCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Overview of the use of data assets in the context of Portuguese companies: Comparison between SMEs and large companiesCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Comparative analysis of welding processes using different thermoplasticsInternational Journal of Integrated Engineering

Mr. Javier Blanco-Romero | Information Theory | Best Researcher Award

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Mr. Javier Blanco-Romero | Information Theory | Best Researcher Award

PhD Student, Carlos III University of Madrid, Spain

Francisco Javier Blanco Romero is a versatile physicist and an active researcher specializing in cryptography, machine learning, robotics, IoT/IIoT, and networks. Currently based in Madrid, he is pursuing a PhD in Telematic Engineering at Universidad Carlos III de Madrid, where he focuses on integrating post-quantum cryptography into secure communication protocols for IoT and IIoT. With a background in physics and robotics, Francisco is dedicated to advancing security in next-generation communication technologies. 🌍🔐

Publication Profile

Education

Francisco holds a Bachelor’s Degree in Physics from Universidad Complutense de Madrid, specializing in fundamental and theoretical physics. He also completed a Master’s Degree in Robotics at Universidad Miguel Hernández de Elche, where his thesis focused on enhancing communication security in ROS 2. He is currently working towards his PhD in Telematic Engineering at Universidad Carlos III de Madrid, researching post-quantum cryptography integration for IoT and IIoT communication protocols. 🎓📘

Experience

Francisco’s professional career includes roles as a Research Support Technician in the QURSA Project at Carlos III University of Madrid, where he focuses on quantum random number generators and post-quantum cryptography for IoT communication. He has also contributed to various EU projects in innovation and technical management, such as the LIFE and Horizon Europe programs. His prior work includes developing a real-time tracking system and GIS for sustainable urban mobility. Francisco also taught programming courses in multimedia and web development. 💻🔍

Awards and Honors

Francisco has been recognized for his contributions to research and development, including his involvement in various prestigious academic events like the RECSI and QSNS conferences. He has authored several publications and has received scholarships for his academic work, such as those from ValgrAI and Carlos III University. 🏆📜

Research Focus

His research is centered on post-quantum cryptography, particularly its application to secure communication protocols for IoT, IIoT, and robotics. Francisco explores quantum-resistant architectures and their integration into modern cryptographic systems to ensure robust security in the face of quantum computing advancements. His ongoing work on machine learning methods for entropy estimation and quantum random number generators contributes to secure data communication in the post-quantum era. 🔒📡

Conclusion

Francisco Javier Blanco Romero is at the forefront of a rapidly evolving field, combining deep knowledge of cryptography, machine learning, and network security. His work promises significant advancements in securing communication systems for IoT, IIoT, and robotics, ensuring their resilience against emerging quantum technologies. He continues to push the boundaries of cryptography and communication security. 🚀🔑

Publications

Machine Learning Predictors for Min-Entropy Estimation
Published: Entropy, 2025-02-02
Link to Article
Cited by: 1

Evaluating Integration Methods of a Quantum Random Number Generator in OpenSSL for TLS
Published: Computer Networks, 2024-12
Link to Article
Cited by: Not yet cited

Integrating Post-Quantum Cryptography into CoAP and MQTT-SN Protocols
Published: IEEE Symposium on Computers and Communications (ISCC), 2024-06-26
Link to Article
Cited by: Not yet cited

PQSec-DDS: Integrating Post-Quantum Cryptography into DDS Security for Robotic Applications
Published: IX Jornadas Nacionales de Investigación en Ciberseguridad, 2024-05
Link to Article
Cited by: Not yet cited

Guided Waves in Static Curved Spacetimes
Published: arXiv preprint, 2024
Link to Article
Cited by: 1

Onion Routing Key Distribution for QKDN
Published: arXiv preprint, 2024-02
Link to Article
Cited by: Not yet cited

Mr. Alvaro Martinez Ballester | Computer vision | Best Researcher Award

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Mr. Alvaro Martinez Ballester | Computer vision | Best Researcher Award

PhD researcher, Miguel Hernández University, Spain

Álvaro Martínez Ballester is a dedicated researcher in the fields of robotics, automation, and deep learning 🤖🎓. Currently working at Universidad Miguel Hernández de Elche as Research Personnel, he specializes in detecting and recognizing dynamic elements using 3D LiDAR and deep learning techniques. His work focuses on improving environmental mapping by eliminating moving objects, making maps more robust and reliable. With a strong academic background and hands-on experience, Álvaro is actively engaged in developing solutions that enhance the capabilities of mobile robotics and autonomous systems 🚀🔬.

Publication Profile

ORCID

🎓 Education

Álvaro holds a Bachelor’s degree in Electronic Engineering and Industrial Automation from Miguel Hernández University of Elche (2021) and a Master’s degree in Robotics from the same university (2022) 🎓🔍. His academic journey is marked by excellence, having achieved a perfect 10/10 score for both his Final Degree and Master’s projects. His research focused on EOG artifact removal in EEG signals and 3D LiDAR-based object detection using deep learning, demonstrating his strong analytical and technical skills 💡📊.

💼 Experience

With a solid foundation in research and industry applications, Álvaro has worked extensively with ROS modules, SLAM, and autonomous robotics 🤖. His previous roles at Universidad Miguel Hernández de Elche include Research Staff, Specialist Technician, and Intern, where he contributed to the development of mapping, control algorithms, and sensor integration for mobile robots 🚀. His expertise in deep learning for object detection and environmental mapping has been instrumental in advancing autonomous robotic navigation 🌍🤖.

🏆 Awards and Honors

Álvaro has demonstrated exceptional academic and research achievements, securing perfect scores (10/10) in his Bachelor’s and Master’s final projects 🏅📚. His dedication to scientific advancements in robotics and automation has positioned him as a promising researcher in the field. His research contributions are being recognized through his work on funded R&D projects and his involvement in cutting-edge LiDAR-based perception systems 🏆🔬.

🔬 Research Focus

Álvaro’s primary research revolves around deep learning for autonomous systems, LiDAR-based perception, and robotic mapping 🚀📡. He is particularly interested in developing advanced algorithms to filter out dynamic elements in real-time, ensuring more reliable environmental understanding for autonomous robots. His work integrates AI, robotics, and sensor fusion, paving the way for future advancements in self-driving technologies and intelligent automation 🤖💡.

🔍 Conclusion

Álvaro Martínez Ballester is a rising expert in robotics, automation, and AI-driven perception 🤖🚀. With a strong academic foundation, hands-on research experience, and innovative contributions to robotic vision and mapping, he is shaping the future of autonomous systems. His work not only advances robotic intelligence but also enhances real-world applications in autonomous navigation and environmental modeling 🌍🔬.

📚 Publication

A Method for the Calibration of a LiDAR and Fisheye Camera SystemApplied Sciences

2025-02-15 | journal-article

Dr. Doljinsuren Enkhbayar | Biomedical Engineering | Best Researcher Award

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Dr. Doljinsuren Enkhbayar | Biomedical Engineering | Best Researcher Award

Ph.D candidate, Department of Biomedical Engineering, Yonsei University, South Korea

Doljinsuren Enkhbayar is a dedicated biomedical engineer specializing in AI-driven healthcare solutions and biomedical signal processing. Born in Ulaanbaatar, Mongolia, she has a strong background in medical equipment engineering and biomedical data science. With years of experience in both academic research and clinical applications, she is currently pursuing her Ph.D. in Biomedical Engineering at Yonsei University, South Korea. Her passion lies in wearable health technology, biosensors, and the integration of machine learning in medical diagnostics.

Publication Profile

Google Scholar

🎓 Education

Doljinsuren’s academic journey began at the Mongolian University of Science and Technology, where she earned a Bachelor of Engineering in Medical Equipment and Aircraft Maintenance Engineering. She further advanced her expertise with a Master of Science in Biomedical Engineering from the same university. Currently, she is a Ph.D. candidate at Yonsei University, South Korea, focusing on AI and machine learning applications in biomedical sciences.

💼 Experience

With a strong foundation in biomedical engineering, Doljinsuren has worked as a Biomedical Engineer at the National Center of Maternal and Child Health of Mongolia, where she specialized in medical equipment management and safety assessments. She later served as a Training Master in the Department of Electrotechnique at the Mongolian University of Science and Technology, contributing to research and mentoring students. Additionally, she played a pivotal role as a secretariat member of the Mongolian Society of Biomedical Engineering, advocating for technological advancements in healthcare.

🏆 Awards and Honors

Doljinsuren has received multiple accolades for her research excellence. She was awarded the Best Paper Award by the Mongolian Young Scientist Association (2022) for her study on electrosurgical unit output power measurement. She also gained international recognition for her work on predicting esophageal varices using platelet count/spleen size ratio, presented at Chulalongkorn University, Thailand (2020). Her research on chronic hepatitis C treatment was featured at Liver Week 2019 in Busan, Korea.

🔬 Research Focus

Her research interests revolve around AI in healthcare, biomedical signal processing, wearable health technologies, and biosensors. She actively explores how machine learning and biomedical data science can enhance diagnostics, patient monitoring, and medical device performance. Her contributions to biomaterials research, particularly chitosan-based sustainable packaging, reflect her interdisciplinary expertise in biomedical applications.

🔍 Conclusion

Doljinsuren Enkhbayar is a rising expert in biomedical engineering and AI-driven healthcare innovations. Her interdisciplinary research, coupled with her clinical and academic experience, positions her at the forefront of modern medical technology advancements. With an unwavering commitment to improving healthcare outcomes through AI and biomedical data science, she continues to push the boundaries of innovation and research excellence.

📚 Publications

Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes – Published in Bioengineering (2025). Read Here

Chitosan Extracted from the Biomass of Tenebrio molitor Larvae as a Sustainable Packaging Film – Published in Materials (2024). Read Here

Oral Administration of Hydrolysed Casein-Based Supplements on Chronic Liver Disease Patients – Published in The Liver Week (2020). Read Here

Significant Effect of Lifestyle Modification Intervention in Patients with Newly Diagnosed Type 2 Diabetes – Published in The Liver Week (2017). Read Here

 

Prof. Danail Brezov | geometric algebras | Best Researcher Award

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Prof. Danail Brezov | geometric algebras | Best Researcher Award

Professor and chief of department, University of Architecture, Civil Engineering and Geodesy, Bulgaria

Dr. Danail Brezov is a distinguished professor and researcher in mathematics, specializing in applied mathematical physics, computational modeling, and artificial intelligence. With a strong academic foundation and a passion for interdisciplinary research, he has contributed significantly to areas such as geometric algebra, numerical simulations, and machine learning applications. His extensive teaching experience spans both university and high-school levels, making mathematics accessible to students of all backgrounds. Driven by curiosity and innovation, he collaborates on projects involving spatial analysis, traffic modeling, and AI-driven data imputation.

Publication Profile

🎓 Education:

Dr. Brezov holds a Ph.D. in Mathematics from the Bulgarian Academy of Sciences (2015), an M.Sc. in Mathematics from Sofia University (2007), and a B.Sc. in Physics from Sofia University (2004). His early education at the Foreign Language School “Romain Rolland” in Stara Zagora equipped him with multilingual proficiency, enhancing his international collaborations.

💼 Experience:

With years of experience in academia and research, Dr. Brezov has held positions at the University of Architecture, Civil Engineering and Geodesy, the National STEM Center, European Polytechnical University, and the British School of Sofia. He has taught a wide range of subjects, including linear algebra, calculus, probability, numerical methods, and machine learning. His expertise extends to applied mathematics in engineering, control systems, geodesy, and AI-driven analytics. His research contributions include developing predictive models, mathematical frameworks, and data-driven solutions for complex systems.

🏆 Awards and Honors:

Dr. Brezov has earned recognition for his outstanding research and teaching contributions. His role as a reviewer for esteemed journals such as AMS, Springer, and Elsevier highlights his academic influence. He has also played a pivotal role in organizing international conferences, research collaborations, and mathematical Olympiads, further cementing his reputation in the field.

🔬 Research Focus:

Dr. Brezov’s research interests span across mathematical physics, Clifford algebras, hypercomplex numbers, and Lie groups. His expertise in computational modeling and AI applications has led to breakthroughs in numerical simulations, cellular automata, and Monte Carlo algorithms. He actively contributes to projects in urban pollution modeling, health analytics, and machine learning-driven optimization. His interdisciplinary approach enables innovative solutions in both theoretical and applied mathematics.

📝 Conclusion:

Dr. Danail Brezov stands as a leading figure in mathematical sciences, blending theory with real-world applications. His contributions to academia, research, and interdisciplinary collaborations continue to shape the fields of mathematics, physics, and AI-driven problem-solving. With a relentless pursuit of knowledge and innovation, he remains dedicated to advancing mathematical research and education on a global scale.

📚 Publications:

The Tragic Downfall and Peculiar Revival of Quaternions. Mathematics, 13(4):637. [Cited by: Mathematics Community] 🔗

Using Rotations to Control Observable Relativistic Effects. Mathematics, 12(11):1676. [Cited by: Relativity Researchers] 🔗

Camera Motion Correction with PGA. Advances in Computer Graphics, Lecture Notes in Computer Science 14498, Springer, Cham. [Cited by: Computer Vision Experts] 🔗

Predicting the Rectal Temperature of Dairy Cows Using Infrared Thermography and Multimodal Machine Learning. Applied Sciences, 13(20):11416. [Cited by: Veterinary and AI Researchers] 🔗

Ensemble Learning Traffic Model for Sofia: A Case Study. Applied Sciences, 13(8):4678. [Cited by: Traffic Engineers] 🔗

Hypercomplex Algebras and Calculi Derived from Generalized Kinematics. Mathematical Methods in the Applied Sciences, 44(17). [Cited by: Mathematical Physicists] 🔗

Factorization and Generalized Roots of Dual Complex Matrices with Rodrigues’ Formula. Advances in Applied Clifford Algebras, 30(29). [Cited by: Algebra Researchers] 🔗

Projective View on Motion Groups I: Kinematics and Relativity. Advances in Applied Clifford Algebras, 29(1-18). [Cited by: Theoretical Physicists] 🔗

Optimization and Gimbal Lock Control via Shifted Decomposition of Rotations. Journal of Applied & Computational Mathematics, 7:410. [Cited by: Robotics Researchers] 🔗

From the Kinematics of Precession Motion to Generalized Rabi Cycles. Advances in Mathematical Physics, Article ID 9256320. [Cited by: Quantum Mechanics Scholars] 🔗

Prof. Yunxia Chen | Intelligent Manufacturing | Best Researcher Award

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Prof. Yunxia Chen | Intelligent Manufacturing | Best Researcher Award

School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, China

Dr. Yunxia Chen is a distinguished professor at Shanghai Polytechnic University, specializing in Materials Science and Engineering. With a Ph.D. from Shanghai Jiaotong University, Dr. Chen has an extensive academic and professional background in advanced welding technologies and materials science. Throughout his career, he has contributed to the field with research focused on the weldability of dissimilar metals, microstructure and mechanical properties of welded joints, and cutting-edge welding technologies. Dr. Chen has worked as a professor, associate professor, and postdoctoral researcher, and has extensive industrial experience as a welding engineer. His academic journey is complemented by his roles in organizing significant international conferences and publishing numerous impactful research papers.

Publication Profile

Scopus

Education:

Dr. Yunxia Chen earned his Ph.D. in Materials Science and Engineering from Shanghai Jiaotong University in 2010, under the supervision of Prof. Shun Yao. His thesis titled “Research of Rapid Prototyping System Based On 3D Scanning Electron Beam” reflects his focus on advanced manufacturing technologies. He completed his M.Sc. in the same field from Dalian Jiaotong University in 2005, where he worked under Prof. Xiongming Zhang on the “Electric Control Study of Conform Production Line Drawing and Rolling Machine.” He received his B.Eng. in Materials Science and Engineering from Dalian Jiaotong University in 1999.

Experience:

Dr. Yunxia Chen has held several prominent academic and professional positions. Since 2024, he has been serving as a professor at Shanghai Polytechnic University. Prior to that, he was an Associate Professor and Professor at Shanghai Dianji University from 2015 to 2023. Dr. Chen also held a postdoctoral position at Shanghai Jiaotong University from 2013 to 2015. Early in his career, he worked as a Welding Engineer at Changchun Railway Vehicles Co., Ltd., from 1999 to 2002. Dr. Chen has also contributed to the academic community by interviewing for significant international conferences, including the 4th International Conference on Robotic Welding, Intelligence, and Automation, in 2014.

Awards and Honors:

Dr. Yunxia Chen’s work has earned him several accolades, reflecting his excellence in research and teaching. He has received awards for his contributions to the field of welding and materials science, including recognition at international conferences and accolades for his innovative research in welding technologies. His research excellence has made a significant impact in both academic and industrial sectors.

Research Focus:

Dr. Chen’s primary research interests lie in the weldability of metals, particularly dissimilar metal welding, and the microstructural and mechanical properties of welded joints. He has extensively explored advanced welding technologies and the effects of welding processes on material properties. His work is pivotal in understanding the behavior of metals during welding and the challenges associated with improving the quality and strength of welded joints. Dr. Chen also investigates the role of microstructure in determining the mechanical properties and performance of materials used in welding.

Conclusion:

Dr. Yunxia Chen’s career stands as a testament to his dedication to advancing materials science and welding technology. His innovative research has paved the way for improvements in the welding industry, addressing both practical and theoretical challenges. Through his academic roles, industrial experience, and research endeavors, Dr. Chen continues to make significant contributions to the field, impacting both the scientific community and industrial practices.

Publications:

Detection of Welding Defects Tracked by YOLOv4 Algorithm
Published: 2025, Applied Sciences
Link: DOI: 10.3390/app15042026

NiFe2O4/Polypyrrole Metacomposites with Tunable Negative Permittivity for Enhanced Electromagnetic Wave Adsorption
Published: 2022, Journal of Materials Science & Technology
Link: Journal of Materials Science & Technology, 108:64-72

Hot Compression Bonding Behavior and Constitutive Model of Spray Deposited 2195 Al-Cu-Li Alloy
Published: 2023, Vacuum
Link: DOI: 10.1016/j.vacuum.2023.111896

A Comparative Study on Microstructural Characterization of Thick High Strength Low Alloy Steel Weld by Arc Welding and Laser Welding
Published: 2023, Materials
Link: Materials 2023, 16, 2212

Microstructure Characterization and Wear Performance of WC-10Co/Ti-6Al-4V Coating Fabricated via Electron Beam Cladding
Published: 2021, Surface and Coatings Technology
Link: DOI: 10.1016/j.surfcoat.2021.127493

Effect of Temperature and Hold Time of Induction Brazing on Microstructure and Shear Strength of Martensitic Stainless Steel Joints
Published: 2018, Materials
Link: DOI: 10.3390/ma1111586

Role of Reversed Austenite Behavior in Determining Microstructure and Toughness of Advanced Medium Mn Steel by Welding Thermal Cycle
Published: 2018, Materials
Link: DOI: 10.3390/ma112127

Metallurgical and Mechanical Properties of Fibrous Laser Welded Thick Q890 High Strength Low Alloy Steel with Varying Weld Geometries
Published: 2022, Journal of Materials Engineering and Performance
Link: DOI: 10.1007/s11665-021-06516-3

Nan Jiang | Property Management | Best Researcher Award

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Mrs. Nan Jiang | Property Management | Best Researcher Award

Prof. Tongji University, China

Nan Jiang is a professor, doctoral supervisor, and Vice Dean of the Shanghai International College of Intellectual Property (SICIP) at Tongji University. Her research spans Intellectual Property and the digital economy, where she serves as the Director of the China Intellectual Property Research Society and the Deputy Director of the National Research Base for the Implementation of Intellectual Property Strategy. With more than 50 SSCI/CSSCI publications, including influential papers in journals such as Science and Public Policy, she has gained recognition for her impactful research. In 2023, she was honored with the Shanghai Oriental Talents Title. 📚🏆

Publication Profile

Scopus

Education

Professor Jiang holds advanced degrees in her field and has earned recognition for her contributions to Intellectual Property (IP) research. Her academic background complements her leadership role at SICIP, where she guides doctoral students and other scholars. 🎓

Experience

With a career dedicated to advancing knowledge in IP and the digital economy, Nan Jiang has led national-level research projects, including those funded by the National Natural Science Foundation of China. As a prominent figure in IP policy, she has consulted for several industries and has collaborated on major national social science projects. 💼🌍

Awards and Honors

Nan Jiang’s contributions have been acknowledged with numerous accolades, including the China Medical Science and Technology Award and the Shanghai Oriental Talents Title in 2023. She has been recognized for her leadership in intellectual property and her groundbreaking research on data markets and digital economy sustainability. 🏅🎖️

Research Focus

Professor Jiang’s research focuses on Intellectual Property and the digital economy, with special interest in green technology, IP policy evaluation, and the intersection of data security with market circulation. Her work plays a crucial role in shaping policies that support sustainable digital economic development. 🌱🔐

Conclusion

Professor Jiang’s expertise in Intellectual Property, combined with her pioneering research in the digital economy, has positioned her as a leader in her field. Her ongoing contributions are paving the way for more innovative and secure digital economies worldwide. 🌟

Publications

A bibliometric analysis of research on organizational resilience

Research on Incentive Mechanisms in the Data Market Based on a Multitask Principal–Agent Model

Evaluating blockchain technology and related policies in China and the USA
A Three-Dimensional Analytical Framework: Textual Analysis and Comparison of Chinese and US Energy Blockchain Policies

Shinoy Vengaramkode Bhaskaran | Big Data Analytics | Best Researcher Award

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Mr. Shinoy Vengaramkode Bhaskaran | Big Data Analytics | Best Researcher Award

Senior Big Data Engineering Manager, Zoom Communications Inc, United States

Shinoy Bhaskaran is a seasoned leader with a strong background in data engineering, platform development, and team leadership. With extensive experience in building large-scale data platforms and driving data strategy, Shinoy specializes in real-time and batch processing using cutting-edge technologies like PySpark, Snowflake, and AWS. He has demonstrated expertise in managing diverse teams globally, fostering high-performance environments, and delivering impactful data-driven solutions across industries. As a Senior Engineering Manager at Zoom Video Communications, he oversees a team of 20+ engineers and has successfully managed data pipelines that process billions of transactions daily. His leadership approach emphasizes mentorship, team growth, and creating inclusive, innovative work cultures. 🌟👨‍💻

Publication Profile

ORCID

Education:

Shinoy Bhaskaran holds a degree in Engineering, but specific details about his educational qualifications are not provided in the available information. His career journey reflects continuous learning and applying new technologies, with an emphasis on real-world problem solving in the data engineering field. 🎓

Experience:

Shinoy’s career spans over a decade, with significant experience in managing data engineering teams and developing robust data platforms. He has worked at prominent organizations such as Zoom Video Communications, GoTo Inc., LogMeIn, Citrix Systems, and Wipro Technologies. In his current role, he manages high-volume data pipelines, focusing on data quality, storage, cost, security, and compliance. He also excels in driving cross-functional collaborations and mentoring teams to achieve high levels of success in data engineering, governance, and analytics. 💼

Awards and Honors:

Shinoy Bhaskaran has been recognized for his excellence in leadership, innovation, and data-driven impact. His work in building and managing large-scale data platforms has earned him respect in the tech community, though specific award details are not provided in the available information. 🎖️

Research Focus:

Shinoy’s research and technical expertise are centered around big data platforms, real-time analytics, cloud computing, data engineering, and data governance. He is particularly interested in developing scalable data solutions for enterprises, ensuring compliance with regulations like GDPR and SOX, and enhancing the decision-making process through data-driven insights. His research spans various domains, including AI-enhanced predictive maintenance, big data analytics for secure banking, and cost optimization strategies for businesses using generative AI. 🔍📊

Conclusion:

Shinoy Bhaskaran’s career is marked by his passion for leadership, technical expertise in data platforms, and commitment to creating high-performing teams. His ability to navigate complex data challenges and deliver impactful solutions has made him a recognized leader in the field of data engineering. 🌟

Publications:

  1. Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization
    Published Year: 2025
    Journal: Computers
    DOI: 10.3390/computers14020059
    Cited by: 0

  2. BankNet: Real-Time Big Data Analytics for Secure Internet Banking
    Published Year: 2025
    Journal: Big Data and Cognitive Computing
    DOI: 10.3390/bdcc9020024
    Cited by: 0

  3. Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework
    Published Year: 2024
    Journal: Sensors
    DOI: 10.3390/s24247918
    Cited by: 0

Savina Mariettou | Cybersecurity in Healthcare | Best Researcher Award

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Ms. Savina Mariettou | Cybersecurity in Healthcare | Best Researcher Award

PhD Candidate, University of the Peloponnese, Greece

Savina Mariettou is a dedicated PhD Candidate at the University of Peloponnese, specializing in healthcare security systems and cryptographic techniques 🔐. With a strong foundation in software engineering and informatics, she has been actively involved in research that enhances the security of healthcare data against cyber threats. Her expertise spans artificial intelligence, machine learning, and data protection, making her a valuable contributor to the field of cybersecurity in healthcare 🚀.

Publication Profile

Google Scholar

🎓 Education:

Savina holds a Master of Science in Informatics for Life Sciences from the University of Patras 🎓, where she focused on medical data mining for coronary heart disease prediction 🏥. She also earned a Bachelor’s degree in Software Engineering from the University of Peloponnese, completing a thesis on the evolution of biomedical ontologies 🔬. Currently, she is pursuing her PhD at the University of Peloponnese, developing advanced cryptographic frameworks to secure healthcare systems against cyber threats 🔑.

💼 Experience:

Savina has worked as a Teaching Assistant at both the University of Peloponnese and the University of Patras, where she supported courses on advanced networking and database systems 📚. She has also contributed as an IT Support Assistant at the General University Hospital of Patras, managing network operations, providing technical support, and ensuring the security of user accounts 💻. Her experience in both academia and IT support has equipped her with hands-on expertise in cybersecurity, data protection, and system maintenance 🔍.

🏆 Awards and Honors:

Savina has actively contributed to cybersecurity and healthcare security research, with her work being recognized in international journals and conferences 🌍. She has participated in prestigious events such as the e-Society 2024 Conference, where she presented her research on security systems in Greek healthcare institutions 🏅.

🔬 Research Focus:

Savina’s research primarily revolves around securing healthcare data using cryptographic and algorithmic approaches 🔎. She explores ways to prevent cyberattacks, ensuring the integrity and confidentiality of sensitive patient information 📊. By integrating artificial intelligence and machine learning into security frameworks, she aims to enhance the resilience of healthcare institutions against cyber threats 🤖.

🔚 Conclusion:

With a passion for cybersecurity and healthcare technology, Savina Mariettou is making significant strides in safeguarding medical data 🔥. Her research, teaching experience, and IT expertise contribute to a more secure and technologically advanced healthcare ecosystem. Through her work, she continues to bridge the gap between cybersecurity and healthcare, ensuring a safer digital future for medical institutions worldwide 🌐.

📚 Publications:

Artificial Intelligence and Algorithmic Approaches of Health Security Systems: A Review

Predicting Coronary Heart Disease through Machine Learning Algorithms

Security Systems in Greek Health Care Institutions: A Scoping Review Towards an Effective Benchmarking

ApproachMachine Learning Improves Accuracy of Coronary Heart Disease Prediction