Jaehyung Kim | Machine Learning | Research Excellence Award

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Mr. Jaehyung Kim | Machine Learning | Research Excellence Award

Division of Fisheries Resources and Environmental Research | South Korea

Jaehyung Kim is a researcher at the West Sea Fisheries Research Institute specializing in fisheries resources and environmental studies. His work integrates machine learning techniques to analyze marine ecosystems, assess species maturity, and support sustainable fisheries management, contributing to data-driven decision-making and innovation in marine science and resource conservation.


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Featured Publications

Estimation of the Length at First Maturity of the Swimming Crab (Portunus trituberculatus) in the Yellow Sea of Korea Using Machine Learning
– Journal of Marine Science and Engineering, 2026

Jihyun Kim | Data-Driven Decision Making | Research Excellence Award

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Ms. Jihyun Kim | Data-Driven Decision Making | Research Excellence Award

Professor | University of Seoul | South Korea

Ms. Jihyun Kim is a researcher in Transportation Engineering with a focus on data-driven analysis of traffic systems and emerging mobility technologies. Her research explores traveler behavior, safety, and operational performance using advanced statistical modeling and simulation-based approaches. She has conducted studies on e-scooter operations on sidewalks using VR simulators to evaluate safety and applicability under realistic conditions. Her work also includes the development of intersection- and roundabout-specific gap acceptance models, incorporating environmental factors such as rainfall. Through her research, she contributes evidence-based insights to support safer, smarter, and more efficient urban transportation systems.

Research Metrics (Google Scholar)

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Featured Publications

Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

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Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

Assistant Professor, Prof. Ramkrishna More Arts, Commerce & Science College, India

Dr. Santosh Jagtap, Assistant Professor at Prof. Ramkrishna More College (Autonomous), is a highly accomplished researcher and academic in the fields of Artificial Intelligence (AI) and Cybersecurity, with extensive expertise in applying AI to smart agriculture, healthcare security, IoT-enabled educational systems, and AI-driven safety solutions. Dr. Jagtap holds advanced academic qualifications and has developed a distinguished research profile that emphasizes practical applications of emerging technologies to address societal challenges. His work integrates machine learning, blockchain, IoT, and real-time data processing, producing innovative solutions in areas such as intelligent irrigation systems, plant disease detection, AI-based emotion recognition for safety alerts, and secure healthcare frameworks. Over his career, Dr. Jagtap has contributed significantly to international research projects and collaborative studies, producing high-impact publications in reputed journals and conference proceedings, such as Materials Today: Proceedings, international conferences on electronics, computing, and applied AI. He has also been recognized for innovation through patent awards, notably for AI-based plant disease identification systems, reflecting his focus on technology transfer and real-world impact. Dr. Jagtap has played an active role in mentoring students, guiding research projects, and participating in professional networks that foster academic and technological growth. He has demonstrated a consistent record of research excellence, with a total of 78 citations across 4 Scopus-indexed publications and an h-index of 3, reflecting the growing impact of his work.

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Featured Publications

  • Jagtap, S. T., Phasinam, K., Kassanu. (2022). Towards application of various machine learning techniques in agriculture. Materials Today: Proceedings, 51, 793–797. 70 citations.

  • Jagtap, S. T., Thakar, (2021). A framework for secure healthcare system using blockchain and smart contracts. Second International Conference on Electronics and Sustainable Technologies. 22 citations.

  • Jagtap, S. T., Jagdale, K. C., & Thakar, C. M. (2023). Identification of plant disease device using artificial intelligence. IN Patent 391523-001. –

  • Pratiksha Bhise, D. S. J., & Jagtap, S. T. (2024). AI-driven emergency response system for women’s safety using real-time location and heart rate monitoring. IJRPR. –

  • Keskar,  A., Jagtap, S. T., et al. (2021). Big data preprocessing frameworks: Tools and techniques. Design Engineering, 1738–1746.

Mr. Sonjoy Ranjon Das | Computer Vision | AI & Machine Learning Award

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Mr. Sonjoy Ranjon Das | Computer Vision | AI & Machine Learning Award

Lecturer,  Global Banking School, United Kingdom

Mr. Sonjoy Ranjon Das (FHEA, MIEEE, MBCS) is a Lecturer in Computing at the Global Banking School, UK, PhD Candidate in Computer Science at London Metropolitan University, and an affiliated researcher with the AI & Data Science Research Group at London Metropolitan University. He is an emerging academic with expertise in artificial intelligence, soft biometrics, cybersecurity, and privacy-preserving surveillance frameworks aligned with ethical AI deployment and GDPR compliance. Mr. Sonjoy Ranjon Das earned his MSc in Cyber Security Technology with Distinction from Northumbria University, UK, following an MBA in Management Information Systems and a BSc (Hons) in Computer Science from Leading University, Bangladesh, which provided him with an integrated background in computing, management information systems, and advanced security practices. Professionally, he has served in diverse higher-education lecturing roles across the UK including Elizabeth School of London, New City College, Shipley College, and other institutions, as well as holding the position of Research Associate on the SoftMatrix and Surveillance (SMS) Project at Northumbria University, contributing to cross-disciplinary and international research. Mr. Sonjoy Ranjon Das’s research interests include privacy-preserving multimodal soft biometrics for identity verification, AI-driven covert surveillance, ethical and GDPR-compliant surveillance technologies, and the fusion of biometrics for crowd analytics in public safety and border security. His research skills encompass advanced machine learning and computer vision techniques, data analytics, Python and Java programming, cloud-IoT integration, and full-stack development, supported by proficiency in data visualization tools such as Power BI, Tableau, and MATLAB.

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Featured Publications

  • Das, S. R., Kruti, A., Devkota, R., & Sulaiman, R. B. (2023). Evaluation of machine learning models for credit card fraud detection: A comparative analysis of algorithmic performance and their efficacy. FMDB Transactions on Sustainable Technoprise Letters. 12 citations.

  • Thinesh, M. A., Varmann, S. S., Sharmila, S. L., & Das, S. R. (2023). Detection of credit card fraud using random forest classification model. FMDB Transactions on Sustainable Technologies Letters. 9 citations.

  • Pranav, R. P., Prawin, R. P., Subhashni, R., & Das, S. R. (2023). Enhancing remote sensing with advanced convolutional neural networks: A comprehensive study on advanced sensor design for image analysis and object detection. FMDB Transactions on Sustainable Computer Letters. 8 citations.

  • Das, S. R., Hassan, B., Patel, P., & Yasin, A. (2024). Global soft biometrics in surveillance: Benchmark analysis, open challenges, and recommendations. Multimedia Tools and Applications. 6 citations.

Zhaoxiang Zhang | Object Tracking | Best Researcher Award

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Prof. Dr. Zhaoxiang Zhang | Object Tracking | Best Researcher Award

Professor at Unmanned System Research Institute, Northwestern Polytechnical University, China

Professor Zhaoxiang Zhang is a distinguished researcher at the Unmanned System Research Institute of Northwestern Polytechnical University. His academic career is characterized by profound contributions to the fields of aerospace engineering, computer vision, and autonomous systems. With a strong foundation in remote sensing and artificial intelligence, Prof. Zhang has emerged as a thought leader in processing point cloud data, developing robust unsupervised learning models, and advancing autonomous navigation technologies. His research has not only contributed to the theoretical development of these fields but also addressed critical real-world challenges in aerospace and defense sectors.

Profile

Scopus

Education

Prof. Zhang pursued his academic training with a strong focus on aerospace technologies, remote sensing, and computational intelligence. His higher education and doctoral research revolved around spaceborne sensing systems, satellite navigation, and sensor fusion. This background equipped him with the analytical and technical foundation to bridge aerospace engineering with cutting-edge AI techniques. His graduate work emphasized image registration and attitude estimation, laying the groundwork for his later innovations in visual navigation and deep learning-based object tracking.

Experience

With years of experience leading both academic and applied research, Prof. Zhang has played a pivotal role in projects funded by the National Natural Science Foundation of China and multiple defense-sector institutions. He has successfully led a Youth Program grant and steered three vertical defense research subjects and two provincial-level initiatives. His research leadership spans the development of advanced deep learning architectures, unsupervised domain adaptation techniques, and lightweight models suitable for embedded aerospace systems. Prof. Zhang also contributes significantly to mentorship, guiding student teams that have earned national innovation awards and top honors at competitions like the Challenge Cup and Internet+ National Games.

Research Interests

Prof. Zhang’s research interests are multidisciplinary, encompassing aerospace target detection and recognition, attitude estimation, point cloud segmentation, multimodal data integration, and unsupervised model transfer. He focuses particularly on non-cooperative target tracking and cross-domain visual matching, crucial for autonomous navigation in dynamic or GPS-denied environments. His work also delves into scene change detection, pixel-level anomaly recognition, and the development of efficient, lightweight neural architectures for real-time applications on UAVs and small satellites. The fusion of AI with aerospace engineering in his work exemplifies a high-impact intersection of disciplines.

Awards

Prof. Zhang’s dedication to innovation and excellence has earned him national recognition. Notably, he has been honored with the Internet+ National Games Silver Award (twice) and the first prize in the prestigious Challenge Cup competition. Under his guidance, research group students have produced outstanding innovation outcomes recognized at the national level. These accolades underline his ability not only to conduct pioneering research but also to cultivate the next generation of innovators in aerospace AI technologies.

Publications

Prof. Zhang has authored over ten SCI-indexed publications as first or corresponding author. Seven of his most notable works include:

  1. Zhang Z, Ji A, Zhang L, et al. (2023). Unsupervised seepage segmentation pipeline based on point cloud projection with large vision model. Tunnelling and Underground Space Technology — cited by 25 articles.

  2. Zhang Z, Xu Y, Song J, et al. (2023). Robust pose estimation for non-cooperative space objects. Scientific Reports — cited by 18 articles.

  3. Zhang Z, Xu Y, Song J, et al. (2023). Planet craters detection using unsupervised domain adaptation. IEEE Transactions on Aerospace and Electronic Systems — cited by 30 articles.

  4. Zhang Z and Zhang L (2023). Rail Surface Defects Detection Using Multistep Domain Adaptation. IEEE Transactions on Systems, Man, and Cybernetics: Systems — cited by 22 articles.

  5. Zhang Z, Ji A, Zhang L, et al. (2023). Deep learning for large-scale point cloud segmentation with causal inference. Automation in Construction — cited by 27 articles.

  6. Zhang Z, Xu Y, Cui Q, et al. (2022). Unsupervised SAR and Optical Image Matching. IEEE Transactions on Geoscience and Remote Sensing — cited by 41 articles.

  7. Song J, Zhang Z, Iwasaki A, et al. (2021). Augmented H∞ Filter for Satellite Jitter Estimation. IEEE Transactions on Aerospace and Electronic Systems — cited by 36 articles.

Conclusion

Professor Zhaoxiang Zhang stands at the forefront of integrating artificial intelligence with aerospace engineering. His extensive contributions in the domains of remote sensing, point cloud processing, and autonomous navigation have significantly advanced both theoretical frameworks and practical applications. As a mentor and leader, his influence extends beyond his own research to shaping the future of technological innovation through his students and collaborations. With a track record of impactful publications, national awards, and strategic project leadership, Prof. Zhang exemplifies the qualities of a transformative scientific thinker deserving of recognition in AI data science.

Sabbir Ahmed Udoy | Artificial Intelligence | Best Researcher Award

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Mr. Sabbir Ahmed Udoy | Artificial Intelligence | Best Researcher Award

Rajshahi University of Engineering & Technology, Bangladesh

Sabbir Ahmed Udoy is an emerging mechanical engineer and researcher with a multidisciplinary focus on sustainable energy systems, environmental optimization, and advanced manufacturing technologies. With a strong foundation in mechanical engineering, Udoy has contributed to diverse research areas that converge on the goal of promoting sustainability through innovative engineering practices. He currently holds a professional position as a Mechanical Engineer at Smile Food Products Limited, where he applies his academic insights to real-world industrial operations. Through active involvement in scholarly publications, hands-on project execution, and collaborative research endeavors, Udoy is establishing himself as a significant early-career contributor to sustainable engineering and energy research.

Profile

Google Scholar

Education

Udoy earned his Bachelor of Science degree in Mechanical Engineering from Rajshahi University of Engineering & Technology (RUET), Bangladesh, completing his academic program in October 2023. He graduated with a CGPA of 3.24 out of 4.0, showing notable improvement in his final semesters, where he achieved a GPA of 3.40 over the last 60 credits. Throughout his undergraduate journey, he combined rigorous coursework with practical learning experiences and research engagements. His capstone thesis focused on evaluating energy consumption and greenhouse gas emissions in textile manufacturing processes, laying the groundwork for his future research trajectory in energy sustainability.

Experience

Professionally, Udoy has been working as a Mechanical Engineer at Smile Food Products Limited since November 2023. In this role, he manages mechanical maintenance and utility operations for the company’s oil refinery plant, emphasizing preventive strategies to optimize performance and minimize downtime. Earlier, he gained industrial exposure through a training stint at the Bangladesh Power Development Board (BPDB), where he was introduced to the operations of a 365 MW dual-fuel combined cycle gas turbine power plant. These hands-on experiences have enriched his engineering acumen and provided him with the ability to bridge theoretical knowledge with industrial applications.

Research Interest

Udoy’s research interests lie at the intersection of energy, sustainability, and technology. His primary focus areas include energy and environmental sustainability, control systems, energy conversion and storage, and additive manufacturing. He is also deeply interested in advanced materials science, machine learning applications in engineering, waste management, and the role of artificial intelligence in achieving sustainable development goals. This wide spectrum of interests highlights his ambition to tackle global engineering challenges using a multidisciplinary lens and cutting-edge technologies.

Award

Udoy’s academic diligence and leadership have earned him several honors. He was the recipient of the Technical Scholarship awarded by RUET, which supported him financially throughout his undergraduate studies. Additionally, he was granted the Education Board Scholarship by the Government of Bangladesh in recognition of his academic achievements. His proactive role as Class Representative and his leadership in student associations like the Society of Automotive Engineers RUET were acknowledged through certificates and crests of appreciation. He also earned multiple certificates for excellence in conference presentations and technical seminars, further showcasing his active academic involvement and communication skills.

Publication

Udoy has co-authored several peer-reviewed journal articles reflecting his research contributions. In 2025, he co-published Harnessing the Sun: Framework for Development and Performance Evaluation of AI-Driven Solar Tracker for Optimal Energy Harvesting in Energy Conversion and Management: X (Impact Factor 7.1), focusing on AI-based solar optimization. In 2024, he contributed to Investigation of the energy consumption and emission for a readymade garment production and assessment of the saving potential in Energy Efficiency (Impact Factor 3.2), emphasizing sustainable apparel manufacturing. Another 2025 publication in the Journal of Solar Energy Research titled Advancements in Solar Still Water Desalination reviewed solar desalination enhancements. He also co-authored An integrated framework for assessing renewable-energy supply chains in Clean Energy (2024, IF 2.9), and Structural analysis and material selection for biocompatible cantilever beam in soft robotic nanomanipulator in BIBECHANA (2023). His latest accepted work (2025) in Environmental Quality Management investigates methane emissions and energy recovery from landfill sites using statistical machine learning. These articles have been cited by multiple scholars and demonstrate the applied relevance and growing recognition of his work.

Conclusion

Sabbir Ahmed Udoy exemplifies the new generation of engineers committed to solving pressing environmental and energy challenges through innovation and interdisciplinary collaboration. His academic training, coupled with industrial experience and a growing body of impactful research, underscores his potential as a thought leader in sustainable engineering. With a forward-looking research agenda and a strong portfolio of scholarly work, Udoy is well-positioned to make lasting contributions to the global discourse on energy efficiency, renewable technologies, and environmentally conscious engineering solutions.

Shoujun Zhou | Artificial Intelligence | Best Scholar Award

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Prof. Shoujun Zhou | Artificial Intelligence | Best Scholar Award

Research Professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Prof. Shoujun Zhou is a distinguished biomedical engineering researcher and a leading figure in the field of medical robotics and image-guided therapy. He currently serves as a specially appointed research professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and concurrently holds a professorship at the National Institute for High-Performance Medical Devices. Over his career, Prof. Zhou has led and contributed to numerous national and provincial-level scientific research projects, focusing on developing interventional surgical robotics and advanced medical imaging technologies. His leadership in this interdisciplinary field has positioned him at the forefront of integrating artificial intelligence with minimally invasive therapeutic solutions.

Profile

Orcid

Education

Prof. Zhou’s academic journey began with a Bachelor’s degree in Test and Control from the Air Force Engineering University (1989–1993). He then earned a Master’s degree in Communication and Information Systems from Lanzhou University (1997–2000), further refining his technical expertise. His academic pursuits culminated in a Ph.D. in Biomedical Engineering from Southern Medical University (2001–2004). This multidisciplinary educational background laid a solid foundation for his future contributions in medical imaging, robotics, and computational modeling.

Experience

With over three decades of professional experience, Prof. Zhou has served in multiple prestigious institutions. From 1993 to 2001, he worked as an engineer in the 94921 Military Unit, followed by a postdoctoral tenure at Beijing Institute of Technology. He transitioned to industry in 2007 as an enterprise postdoctoral researcher at Shenzhen Haibo Technology Co., Ltd., and later joined the 458 Hospital of the PLA as a senior engineer. Since 2010, he has been a principal investigator and research professor at SIAT, where he leads a dedicated research team working on the convergence of robotics, imaging, and AI for medical applications.

Research Interest

Prof. Zhou’s research primarily focuses on interventional surgical robots, image-guided therapy, and medical image analysis. He is particularly interested in developing intelligent, minimally invasive systems that combine AI algorithms with real-time imaging for precise diagnostics and interventions. His work includes modeling and segmentation of vascular structures, semi-supervised learning techniques in medical imaging, and the development of surgical robots tailored for procedures such as liver tumor ablation and cardiovascular interventions. He is also actively involved in improving navigation systems that reduce or eliminate radiation exposure in image-guided procedures.

Award

Prof. Zhou’s contributions have been widely recognized both nationally and internationally. He was honored with the “Best Researcher Award” at the Global Awards on Artificial Intelligence and Robotics in 2022, organized by ScienceFather. He also received a Silver Medal in the Global Medical Robot Innovation Design Competition in 2019 for his work on a vascular interventional robotic system. His earlier work earned the Second Prize of Guangdong Provincial Science and Technology Progress Award in 2009 and contributed to a project that received a First-Class Prize in Science and Technology Progress from the Ministry of Education in 2006. These accolades reflect his sustained excellence and impact in the field of medical technology.

Publication

Prof. Zhou has authored over 100 scientific papers, including several published in top-tier journals. Selected key publications include:

  1. Zhang Z. et al. (2024). “Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation,” Bioengineering, 11(10):1031 – cited in spinal image AI segmentation studies.

  2. Zhang X. et al. (2024). “Automatic Segmentation of Pericardial Adipose Tissue from Cardiac MR Images,” Medical Physics, DOI:10.1002/mp.17558 – referenced for semi-supervised MR image segmentation.

  3. Tian H. et al. (2024). “EchoSegDiff: a diffusion-based model for left ventricular segmentation,” Medical & Biological Engineering & Computing, DOI:10.1007/s11517-024-03255-0 – cited in cardiac echocardiography image modeling.

  4. Li J. et al. (2024). “DiffCAS: Diffusion based Multi-attention Network for 3D Coronary Artery Segmentation,” Signal, Image and Video Processing, DOI:10.1007/s11760-024-03409-5 – relevant in coronary CT imaging analysis.

  5. Wang K.N. et al. (2024). “SBCNet: Scale and Boundary Context Attention for Liver Tumor Segmentation,” IEEE Journal of Biomedical and Health Informatics, 28(5):2854-2865 – cited in liver tumor segmentation research.

  6. Xiang S. et al. (2024). “Automatic Delineation of the 3D Left Atrium from LGE-MRI,” IEEE Journal of Biomedical and Health Informatics, DOI:10.1109/JBHI.2024.3373127 – frequently cited in atrial structural analysis.

  7. Miao J. et al. (2024). “SC-SSL: Self-correcting Collaborative and Contrastive Co-training,” IEEE Transactions on Medical Imaging, 43(4):1347-1364 – referenced in semi-supervised medical image learning.

Conclusion

Prof. Zhou’s work exemplifies the synergy between engineering and medical science, enabling significant advances in minimally invasive diagnosis and treatment. Through his persistent innovation in surgical robotics and medical image computing, he has made a profound impact on the evolution of intelligent healthcare technologies. His dedication to mentoring young researchers and contributing to national and provincial projects reflects a commitment not only to scientific discovery but also to the translation of research into clinical and industrial applications. With a career marked by excellence in research, education, and innovation, Prof. Zhou continues to be a pivotal figure shaping the future of intelligent medicine.

Romuald Rzadkowski | Signal Processing | Best Researcher Award

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Prof. Romuald Rzadkowski | Signal Processing | Best Researcher Award

Head of Aeroelastic Department at Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Poland

Professor Romuald Rzadkowski is a renowned figure in the field of fluid mechanics and turbomachinery, recognized for his extensive research contributions and academic leadership. As a full professor and the Head of the Aeroelastic Department at the Institute of Fluid-Flow Machinery, Polish Academy of Sciences in Gdansk, he has spent decades advancing the science of unsteady aerodynamics, structural dynamics, and diagnostics in rotating machinery. In his career, he has authored over 200 scientific papers, written 20 books, and edited two, influencing both theoretical frameworks and industrial applications. His academic involvement is complemented by service as Vice-Editor of the Journal of Vibration Engineering and Technologies and an active role in organizing the VETOMAC conference series.

Profile

Scopus

Education

Professor Rzadkowski holds dual Master’s degrees, reflecting his interdisciplinary expertise. He earned an MSc in Engineering from the Gdansk University of Technology in 1978 and later completed an MSc in Mathematics at the University of Gdansk in 1983. These foundational studies established a strong base in both applied mechanics and theoretical analysis. He continued his academic journey by obtaining a PhD in 1988 from the Institute of Fluid-Flow Machinery at the Polish Academy of Sciences, followed by a Doctor of Science (DSc) degree in 1998 from the same institution. This academic progression underscores his commitment to deepening scientific understanding across fluid dynamics and structural mechanics.

Experience

Since joining the Institute of Fluid-Flow Machinery at the Polish Academy of Sciences in 2004 as a full professor, Professor Rzadkowski has led the Aeroelastic Department with a focus on cutting-edge research and innovation in turbomachinery. His career spans decades of experience not only in academia but also in collaborative industrial research. He is a Fellow of the International Federation for the Promotion of Mechanism and Machine Science (IFToMM) and actively contributes to the ASME Committee on Structures and Dynamics. His mentorship has guided 14 doctoral candidates to successful dissertations, cultivating the next generation of researchers. Moreover, his leadership in organizing major international conferences highlights his dedication to knowledge dissemination and global collaboration.

Research Interest

Professor Rzadkowski’s research interests lie at the intersection of fluid dynamics and mechanical engineering, particularly in the dynamics of turbomachinery. His work has significantly contributed to the understanding of life estimation of turbine blades under operational stress conditions, both steady and unsteady. He is a pioneer in analyzing and mitigating flutter and nonsynchronous vibrations in turbine stages and has developed innovative signal processing techniques, including tip-timing algorithms, for monitoring and diagnosing complex rotor systems. His contributions extend to the development of systems that assess and predict remaining component life following mechanical failures, making his work valuable for both academic and industrial stakeholders in the energy sector.

Award

Throughout his illustrious career, Professor Rzadkowski has been recognized for his scientific excellence and international impact. While specific awards are not detailed here, his election as a Fellow of IFToMM and his involvement in the ASME Committee on Structures and Dynamics speak to his global reputation and recognition among peers. His role as a Vice-Editor and conference organizer further illustrates the esteem in which he is held in the scientific community.

Publication

Among his recent notable publications are:

  1. Multimode Tip-Timing Analysis of Steam Turbine Rotor Blades, IEEE Sensors Journal, 2023 – cited by 19 articles.

  2. Nonsynchronous Rotor Blade Vibrations in Last Stage of 380 MW LP Steam Turbine at Various Condenser Pressures, Applied Sciences (Switzerland), 2022 – cited by 18 articles.

  3. An Optimal Parameter Identification Approach in Foil Bearing Supported High-Speed Turbocharger Rotor System, Archive of Applied Mechanics, 2021 – cited by 14 articles.

  4. Computational Fluid Dynamics Analysis of Several Designs of a Curtis Wheel, Archives of Thermodynamics, 2021 – 0 citations.

  5. Computational Fluid Dynamics Analysis of 1 MW Steam Turbine Inlet Geometries, Archives of Thermodynamics, 2021 – cited by 5 articles.

  6. Design and Investigation of a Partial Admission Radial 2.5-kW Organic Rankine Cycle Micro-Turbine, Archives of Thermodynamics, 2021 – cited by 19 articles.

  7. Tip-Timing Measurements and Numerical Analysis of Last-Stage Steam Turbine Mistuned Bladed Disc During Run-Down, Archives of Thermodynamics, 2021 – cited by 19 articles.

Conclusion

Professor Romuald Rzadkowski’s academic and research legacy is a testament to his lifelong commitment to solving some of the most challenging problems in turbomachinery and structural dynamics. Through innovative methods in unsteady flow modeling, signal diagnostics, and failure life estimation, he has significantly enhanced the predictive maintenance and safety standards of rotating machinery. His influence is further magnified through his extensive publication record, global collaborations, editorial leadership, and dedicated mentorship. As a thought leader in his field, he continues to shape the future of aeroelastic research and mechanical diagnostics with both academic rigor and industrial relevance.

Corneliu Barbulescu | AI for IT Operations | AI Breakthrough Award

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Mr. Corneliu Barbulescu | AI for IT Operations | AI Breakthrough Award

Executive Architect at IBM, Romania

Corneliu Nicolae Barbulescu is a distinguished architecture leader with over two decades of experience in transforming organizations through innovative IT strategies and enterprise-level architecture. With deep technical expertise and strategic foresight, he has consistently delivered complex IT systems across diverse industries and geographies. Recognized for his leadership at IBM, where he serves as Lead Enterprise Architect and Cloud & DevSecOps Competency Center Leader, Barbulescu is known for his contributions to cloud architecture, application modernization, and enterprise digital transformation. His work spans Europe, the Middle East, and Africa, bringing cutting-edge technologies like AI, RPA, and cloud-native applications into critical government and enterprise projects.

Profile

Orcid

Education

Corneliu holds a Master of Science degree in Software Project Management (2002) and a Bachelor’s degree in Computer Science for Economics (1997), both from the Academy of Economic Studies, Faculty of Cybernetics, Romania. His academic foundation in economics and software engineering positioned him to bridge business goals with technological execution effectively. Complementing his formal education, Barbulescu has acquired several prestigious certifications, including TOGAF 8, Azure Cloud Certification, and IBM’s Architect Profession Certification – Level 3 Thought Leader. His status as an IBM Senior Inventor and member of the IBM Academy of Technology demonstrates his ongoing commitment to professional development and innovation leadership.

Experience

Barbulescu’s professional journey spans from software development to enterprise architecture leadership. He began his career in Romania at Totalsoft, advancing from developer to software architect and contributing to the creation of a renowned ERP product. At IBM, he has held multiple influential roles, including Executive Architect in the Europe Cloud Tiger Team and CEE Cloud CTO. His expertise has shaped critical digital transformation programs for clients such as the European Commission, Skoda, and major telecommunications and insurance companies. His strategic leadership in programs like Project ‘Accelerate’ and the “Move to Cloud” initiative for EU agencies showcases his ability to navigate complex multicloud environments and guide enterprise-wide changes.

Research Interest

Corneliu’s research interests align with enterprise architecture evolution, cloud-native transformations, DevSecOps integration, and the application of artificial intelligence in IT operations. He is particularly focused on enabling operational efficiency through automation and intelligent tooling, and has recently contributed to AI pilot projects designed to enhance root cause analysis and incident resolution in IT support environments. His innovation-driven mindset is evident in his patent contributions and his leadership roles in IBM’s invention development teams, especially within cloud and robotic process automation domains.

Award

Throughout his career, Corneliu has received numerous accolades recognizing his technical excellence and service contributions. He has been honored with seven Outstanding Service Awards by IBM, reflecting his role in strategic client engagements and internal technology advancement. His appointments as a Blue Core Mentor and Technical Delivery Assessor further affirm his influence within IBM’s technical community. Notably, he is a co-founder of the Technical Expert Council Romania and an active contributor to the Association of Open Group Enterprise Architects (AOGEA).

Publication

Corneliu Nicolae Barbulescu has authored several impactful publications that highlight his technical insights and enterprise architecture expertise. Notable publications include:

  1. “Education, Research and Business Technologies” – Proceedings of the 21st International Conference on Informatics in Economy (IE 2022), 2022 – cited by several works in digital transformation studies.

  2. “Move to Cloud of Enterprise Applications: large EU organisation case study”, 2022 – published in a leading digital transformation journal, this case study is frequently cited in cloud migration literature.

  3. “Digital Enterprise Reference Architecture for Financial Institutions”, 2021 – published in the Journal of Enterprise Architecture, cited for its innovative framework.

  4. “A Comparative Analysis of Cloud Transformation Patterns”, 2020 – published in Cloud Computing Advances, referenced in both academic and professional forums.

  5. “DevSecOps Toolchains for Hybrid Environments”, 2020 – presented at the European Cloud Conference, noted for practical deployment insights.

  6. “ERP Cloudification and SaaS Design Principles”, 2019 – published in the International Journal of Software Engineering, cited in ERP transformation research.

  7. “Containerization Strategies for Regulated Sectors”, 2018 – published in Cloud Security Review, relevant for compliance-focused industries.

Conclusion

Corneliu Nicolae Barbulescu exemplifies technical leadership in the field of enterprise IT architecture. His work at IBM and with multiple high-profile clients demonstrates a unique ability to transform legacy systems into agile, scalable cloud-native solutions. With an academic background that blends economics and computer science, and a professional path marked by international influence, strategic foresight, and technical excellence, Barbulescu continues to be a pioneering force in IT architecture and transformation. His contributions to research, innovation, and practical enterprise solutions underscore a career built on vision, rigor, and real-world impact.

Rajender Singh | Machine Learning and Communication | Best Academic Researcher Award

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Mr. Rajender Singh | Machine Learning and Communication | Best Academic Researcher Award

Assistant Professor at JEC, Jabalpur, India

Rajender Singh Yadav is a distinguished academician and researcher with over two decades of experience in the field of Electronics and Communication Engineering. He received his Bachelor of Engineering degree from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, in 2001, and later completed his Master of Technology from the same university in 2010. Presently, he is serving as an Assistant Professor at BGIEM, Jabalpur, where he has been contributing to academic and research activities since March 2022. Throughout his career, he has demonstrated expertise in various cutting-edge areas such as Artificial Intelligence, Robotics, Embedded Systems, and Signal and Image Processing. His dedication to education and research has significantly impacted both students and the academic community.

Profile

Orcid

Education

Rajender Singh Yadav’s academic foundation is firmly rooted in Electronics and Communication Engineering. He began his academic journey at HCET, Jabalpur, Madhya Pradesh, where he pursued his B.E. from 1997 to 2001, equipping himself with essential engineering skills and a solid understanding of communication technologies. To further enhance his expertise, he enrolled in UPTU, Lucknow, where he completed his M.Tech. in Electronics and Communication Engineering between 2007 and 2010. His advanced studies allowed him to deepen his knowledge of sophisticated communication systems, embedded technologies, and AI-driven processes, laying a strong groundwork for his future research endeavors and teaching career.

Experience

With an extensive teaching career spanning over 22 years, Rajender Singh Yadav has amassed a wealth of experience across reputed institutions. He started as a Lecturer at GNIT, Greater Noida, in 2003, where he served for two years. Following this, he worked at AKGEC, Ghaziabad, as a Lecturer and later as an Assistant Professor from 2005 to 2012. His commitment to academic excellence led him to GGITS, Jabalpur, where he spent a decade nurturing young minds as an Assistant Professor. Since 2022, he has been associated with BGIEM, Jabalpur, continuing his journey of mentoring students and advancing research. Over the years, he has successfully blended academic teaching with research innovations, fostering a learning environment focused on technological advancement and real-world application.

Research Interest

Rajender Singh Yadav’s research interests are broad and interdisciplinary, focusing on AI, Robotics, Embedded Systems, and Signal and Image Processing. His passion lies in developing intelligent systems capable of addressing real-time challenges in wireless communication, autonomous robotics, and integrated system designs. He actively explores the synergy between artificial intelligence and hardware systems to optimize performance, reliability, and energy efficiency. His research delves deep into areas like deep reinforcement learning, optimized channel bonding, and intelligent transmit power control mechanisms, all aimed at enhancing wireless network efficiency. His work reflects a keen understanding of current technological trends and a vision for future innovations in electronics and communication engineering.

Award

Although specific awards have not been documented, Rajender Singh Yadav’s professional journey itself stands as a testament to his dedication and excellence. His consistent progression through reputed institutions, long-standing teaching career, and contribution to the academic field highlight the recognition and trust he has garnered within the educational community. His involvement in publishing impactful research in reputed international journals showcases his commitment to scholarly excellence and innovation.

Publication

Rajender Singh Yadav has contributed notably to academic literature. One of his significant publications is titled “Joint Optimization of Channel Bonding and Transmit Power Using Optimized Actor–Critic Deep Reinforcement Learning for Wireless Networks”, published in the International Journal of Communication Systems on May 10, 2025. This research explores the integration of optimized actor–critic deep reinforcement learning models to simultaneously enhance channel bonding and transmit power efficiency in wireless networks. The article has already begun to gain citations and is recognized for its practical approach to complex wireless communication challenges. This work stands out for its novel methodology and potential applications in next-generation network systems, demonstrating his ability to merge theoretical research with practical technological needs.

Conclusion

In conclusion, Mr. Rajender Singh Yadav is a seasoned educator and dedicated researcher whose contributions to Electronics and Communication Engineering have been remarkable. With a solid academic background, a wealth of teaching experience, and a keen interest in advanced research areas like AI and embedded systems, he continues to influence and inspire the academic and research communities. His efforts in mentoring students, developing innovative research solutions, and publishing impactful studies reflect his unwavering commitment to advancing technology and education. As he moves forward in his career, his passion for innovation and excellence promises to bring about significant contributions to the field of communication engineering and beyond.