Mittar Pal | Engineering | Women Researcher Award

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Dr. Mittar Pal | Engineering | Women Researcher Award

Deenbandhu Chhotu Ram University of Science and Technology | India

Dr. Mittar Pal is an experienced academic and researcher in Electronics & Communication Engineering with over twelve years of teaching and research experience, specializing in renewable energy systems and AI‑based engineering applications. He holds a B.Tech in ECE (2003), M.Tech in Nanoscience & Technology (2013) and completed his Pre‑PhD in ECE (2019) from renowned Indian institutions, and recently earned his PhD on barrier identification and prioritisation for solar photovoltaic system deployment in dairy farming in India (2023). His work on techno‑economic analysis of photovoltaic systems in dairy farming and optimization of utility‑integrated solar PV systems has appeared in SCI and Scopus‑indexed outlets, and he has supervised numerous B.Tech and M.Tech projects while contributing to NBA documentation and curriculum development. He is UGC‑NET qualified for Electronic Science (Assistant Professor). His research interests span signal & system theory, digital electronics, power electronics, renewable solar energy modelling (using MATLAB, HOMER Pro, SAM, RETScreen), AI/ML, generative AI, IoT and pattern recognition. With a growing scholarly profile (h‑index ~ 5 and citation count ~5 as per publicly listed profiles), he continues to publish, present at international conferences, and drive innovation in teaching and research. His dedication to transforming traditional dairy farming through solar PV integration underscores his commitment to sustainability and engineering education.

Profile: Scopus 

Featured Publications

Mittarpal. (2018). “Modeling and Simulation of Solar Photovoltaic Module using Matlab-Simulink.” International Journal for Research in Engineering Application & Management .

Mittarpal. (2018). “Modeling Design and Simulation of Photovoltaic Module with Tags Using Simulink.” International Journal of Advance & Innovative Research.

Mittarpal, & Asha. (2018). “Simulation and Modeling of Photovoltaic Module Using Simscape.” National Conference on Advances in Power, Control & Communication Systems .

Mittarpal, Naresh Kumar, & Priyanka Anand, Sunita. (2017). “Realization of Flip Flops Using LabVIEW and MATLAB.”

Mittarpal, Naresh Kumar, & Sunita Rani. (2017). “Realisation of Digital Circuits Systems Using Embedded Function on MATLAB.” International Journal of Engineering and Technology.

Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

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Dr. Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

Georgia Southern University | United States

Dr. Chulhwan C. Bang is an Assistant Professor of Business Analytics and Information Systems at Georgia Southern University. He earned his Ph.D. in Business Management, specializing in Management Science and Systems with a minor in Communication, from the University at Buffalo, SUNY. With over a decade of academic and professional experience, Dr. Bang has taught a wide range of courses in business programming, information systems, and data analytics, integrating tools such as Python, SAP, Power BI, and Tableau. His research interests include big data analytics, cryptocurrency forecasting, social media analysis, deep learning, and sports analytics. He has published in top-tier journals such as Information Systems Frontiers and International Journal of Information Management and actively collaborates with students on applied data-driven projects. Prior to academia, he worked in the IT industry as a system architect and software developer, contributing to large-scale ERP and BI projects in Korea and the U.S. Dr. Bang has received multiple honors, including the Outstanding Research Award and finalist recognition for accelerator research grants. His work bridges theory and practice, fostering innovation in analytics education and advancing interdisciplinary research in business intelligence and emerging technologies.

Profile : Orcid

Featured Publications

Lee, Y. S., & Bang, C. C. (2022). Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network. Information Systems Frontiers.

Bang, C. C., Lee, J., & Rao, H. R. (2021). The Egyptian protest movement in the twittersphere: An investigation of dual sentiment pathways of communication. International Journal of Information Management.

Bang, C. C. (2020). Predicting Loyalty of Korean Mobile Applications: A Dual-Factor Approach. International Journal of Information and Communication Technology for Digital Convergence (IJICTDC).

Yu, J., Bang, C. C., & Oh, D.-Y. (2020). The Effect of Noncognitive Factors on Information Disclosure on Social Network Websites: Role of Habit and Affect. Southern Business & Economic Journal.

Kwon, K. H., Bang, C. C., Egnoto, M., & Rao, H. R. (2016). Social media rumors as improvised public opinion: semantic network analyses of Twitter discourses during Korean saber rattling 2013. Asian Journal of Communication.

Ying Jin | Big Data Analytics | Best Researcher Awards

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Ying Jin | Big Data Analytics | Best Researcher Award

Professor, Nanjing University, China

Profile

 Scopus 

Prof. Jin Ying is a Professor at the Department of Computer Science and Technology, Nanjing University, widely recognized for her leadership and contributions in computer education, data mining, citation analysis, big data, and virtual reality applications. Her career bridges teaching, research, and academic service, reflecting a strong commitment to advancing both theoretical knowledge and practical innovations in the field of computer science. She has served in multiple influential academic and professional roles, helping shape the direction of education and technology integration in China.

Education

Prof. Jin began her academic journey in geochemistry and later transitioned into information management and computer science, bringing an interdisciplinary perspective to her work. She earned her Ph.D. in Management with a specialization in data mining and CSSCI research, which laid the foundation for her impactful contributions in citation analysis, big data, and education technology. Her diverse educational background allows her to integrate cross-disciplinary insights into computer science education and applied research.

Experience

Throughout her career at Nanjing University, Prof. Jin has advanced from teaching assistant to lecturer, associate professor, and eventually full professor. She teaches a wide range of courses including computer applications, Visual Basic, Python, and C programming, with her pedagogy focusing on innovation and practical engagement. Beyond the classroom, she serves as Group Lead of Visual Basic and Secretary of the Center of College Computer Test in Jiangsu Province. She is also an active member of the Computer Education Supervisory Committee (MOE, Liberal Arts), Jiangsu Computer Foundation Education Committee, and the Council on East China University Computer Foundation Education. Additionally, she contributes as a judge for the National College Computer Design Competition and as a peer reviewer for CSSCI-indexed journals.

Research Interests

Prof. Jin’s research integrates education and technology, addressing critical issues such as AI-driven talent training models, programming pedagogy reform in the AI era, flipped classroom strategies, big data course design for non-computer majors, and innovations in youth IT education. She has published widely in international journals and conferences, making significant contributions to the fields of data mining, education reform, and computational thinking. Her authored teaching resources, including College Basic Computer Applications and New Visual Basic Programming, are used across universities and contribute to improving computer education nationwide.

Awards

Prof. Jin’s achievements have been recognized through numerous awards and honors. She received the prestigious First Tan Haoqiang Computer Education Fund Outstanding Teacher Award and Nanjing University’s Shilin Teaching Award, reflecting her excellence in teaching and mentorship. She has also earned multiple best paper awards and nominations at international conferences, alongside prizes for guiding student projects in national-level computer design competitions. These recognitions highlight her dual impact as both a researcher and educator.

Featured Publications

  • Jin, Y. (2024). Exploration of K12 Multi-level Information and AI Talent Training Model.

  • Jin, Y. (2024). Exploration on Teaching Content Reform of Programming Course in the Era of AI.

  • Jin, Y. (2024). A survey of research on several problems in the RoboCup3D simulation environment.

  • Jin, Y. (2023). The Role of Science and Technology Innovation Competition in Talent Cultivation and Development.

  • Jin, Y. (2022). An approach for evaluating course acceptance based on Bayesian network. Int. J. of Intelligent Internet of Things Computing.

  • Jin, Y. (2022). Design and Implementation of a Cloud-Native Platform for Financial Big Data Processing Course.

  • Jin, Y. (2022). Hierarchical and Diverse Cultivation of Data Thinking Capability in College Based on New High School Curriculum Standards.

Conclusion

By combining rigorous scholarship, innovative teaching, and impactful leadership, Prof. Jin Ying has significantly advanced computer education reform and promoted the integration of technology with pedagogy. Her interdisciplinary vision and ability to merge data-driven methods with educational practice have influenced generations of students, equipping them with computational skills essential for the digital age. Through her roles in research, teaching, academic committees, and national projects, she continues to shape the landscape of computer science education in China and beyond, fostering a forward-looking environment that bridges research, practice, and innovation.

Maksym Lazirko | Accounting Information Systems | Best Academic Researcher Award

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Prof. Maksym Lazirko | Accounting Information Systems | Best Academic Researcher Award

Rutgers University | United States

Prof. Maksym Orest Lazirko is an emerging scholar and academic professional specializing in Management Information Systems, Accounting Information Systems, and advanced technologies impacting modern business practices. With a multidisciplinary foundation spanning management, accounting, geological sciences, and quantum computing, he has developed a unique expertise that bridges technical innovation and business strategy. His academic and professional journey reflects a strong commitment to research, teaching, and technological transformation in accounting and audit domains. Prof. Lazirko actively engages in developing frameworks for blockchain applications, ESG (Environmental, Social, and Governance) reporting, quantum computing integration in accounting systems, and data-driven audit methodologies. His work emphasizes innovative approaches to automation, artificial intelligence, and emerging technologies that redefine corporate reporting and decision-making.

Professional Profiles

SCOPUS
ORCID

Education

Prof. Lazirko completed his undergraduate studies with a Bachelor of Science in Management of Information Systems and a minor in Geological Science. Building upon his academic foundation, he pursued advanced research as a Doctoral Candidate in Management with a concentration in Accounting Information Systems at Rutgers University, where he has made significant contributions under the mentorship of Dr. Miklos Vasarhelyi. His educational background reflects a blend of business management, technological innovation, and applied sciences, equipping him with the expertise to address interdisciplinary challenges in the digital and corporate ecosystem.

Experience

Prof. Lazirko has amassed extensive teaching, research, and industry-related experience across multiple roles, including instructor, research assistant, teaching assistant, and guest lecturer at Rutgers University. His teaching portfolio spans courses such as Audit Analytics, Managerial Accounting, Financial Accounting, Data Warehousing & Data Mining, Management Information Systems, and Advanced Design & Development of Information Systems. His instructional expertise integrates theory with cutting-edge technological tools, providing students with practical and forward-thinking insights into accounting and information systems. Beyond academia, he has held roles in child development and robotics education, aquatics, and geology-focused positions, where he honed his leadership, process improvement, and technical skills. His volunteering work as a leader and advisor at a nonprofit organization reflects his dedication to community service, operational support, and technological guidance.

Research Interests

Prof. Lazirko’s research interests focus on the convergence of emerging technologies and accounting systems. His primary areas include quantum computing applications in accounting, blockchain-based proof of reserves frameworks, ESG-focused corporate reporting methodologies, automation in audit processes, metaverse and augmented/virtual reality applications in information systems, and artificial intelligence integration for financial transparency. He has contributed to developing methodologies for monitoring and reporting Natech disasters for business continuity, advanced risk assessment in cryptocurrency markets, and innovative designs for academic advisory chatbots. His interdisciplinary approach aims to bridge gaps between technological potential and practical business needs in an evolving regulatory landscape.

Awards and Contributions

Prof. Lazirko has been recognized for his active participation in professional conferences, workshops, and peer review activities in the field of accounting and information systems. He has served as a moderator, discussant, and organizer at significant academic meetings, including AAA Mid-Year Meetings, Transformative Technology Workshops, and WCARS conferences. His contributions as a volunteer referee for leading journals such as The British Accounting Review, Accounting Horizons, and the Journal of Emerging Technologies in Accounting reflect his standing as a critical contributor to scholarly discourse and research development. Furthermore, his involvement in the creation of innovative educational platforms such as quantum computing courses for business students and virtual reality classrooms highlights his forward-thinking contributions to academic innovation.

Publications

Lazirko, M., Appelbaum, D., & Vasarhelyi, M. (2025). “Proof of Reserves: A Double-Helix Framework” in The British Accounting Review.

Lazirko, M. (2025). “The Quantum Dynamics of Cost Accounting: Investigating WIP via the Time-Independent Schrödinger Equation” in Journal of Decision Science and Optimization.

Lazirko, M., & Gates, A. (2025). “Unveiling Nature’s Fury: Natech Disasters for Business – A Continuous Monitoring & Reporting Framework” in Journal of Risk Research.

Conclusion

Prof. Maksym Orest Lazirko embodies the intersection of technology, research, and education, actively shaping the future of accounting and information systems. His work reflects a continuous pursuit of integrating next-generation technologies—quantum computing, blockchain, artificial intelligence, and immersive systems—into the financial and corporate sectors. Through his teaching, research, and community engagement, he promotes the advancement of sustainable, transparent, and innovative business practices. His ongoing efforts in developing cutting-edge frameworks and educational initiatives position him as a valuable thought leader in the fields of accounting innovation, digital transformation, and academic mentorship.

Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

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Dr. Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

Yangzhou University | China

Dr. Muhammad Saddam Khokhar is an accomplished academic and researcher specializing in generative artificial intelligence and computer vision. With over a decade of teaching, research, and leadership experience, he has made significant contributions to artificial intelligence, quantum computing, and deep learning. His expertise spans across developing innovative AI-driven solutions, managing academic programs, and mentoring research scholars at undergraduate, postgraduate, and doctoral levels. As an assistant professor and former department chairman, he has been instrumental in advancing artificial intelligence education, accreditation processes, and research-driven innovation in multiple institutions internationally.

Professional Profiles

ORCID

GOOGLE SCHOLAR

Education

Dr. Khokhar earned his Doctorate in Computer Application Technology from Jiangsu University, China, where his dissertation focused on nonlinear optimization and dimensional reduction using advanced Spearman correlation analysis integrated with deep learning models. His research was recognized with an excellent dissertation award for its innovative methodologies. He also holds a Master’s degree in Computer Science and Information Technology with a focus on machine learning, data mining, and software project management, as well as a Bachelor’s degree in Software Engineering, where he developed strong expertise in artificial intelligence, software architecture, and advanced programming techniques.

Experience

With extensive academic and professional experience, Dr. Khokhar has served in multiple teaching and research roles, including Assistant Professor at the College of Artificial Intelligence, Yangzhou University, and Postdoctoral Fellow at the College of Software Engineering, focusing on generative AI projects. He has also chaired the Department of Artificial Intelligence at Dawood University of Engineering and Technology and contributed to curriculum development, laboratory design, and accreditation processes for AI and quantum computing programs. Earlier in his career, he held lecturer positions at leading Pakistani universities and worked as a software engineer, gaining industry insights that enriched his academic pursuits.

Research Interests

His research primarily focuses on generative artificial intelligence, computer vision, deep learning, and nonlinear optimization techniques. Dr. Khokhar has developed innovative models leveraging Spearman correlation analysis for medical image processing, robotic vision, traffic surveillance, and multi-camera monitoring systems. His recent projects explore lightweight generative adversarial networks (IoTGAN), hybrid attention-driven generative frameworks, and blockchain-based secure election systems. He has also actively contributed to discussions on artificial general intelligence, metaverse technologies, and ethical implications of AI in modern societies through various publications and invited talks.

Awards

Dr. Khokhar has been recognized with several prestigious awards for his contributions to innovation, research, and academic excellence. These include the Best Innovation Award for developing a revolutionary AI platform for gene editing and medical technology, multiple academic achievement awards during his doctoral studies, and accolades in application development and research competitions. His work has been published in high-impact journals and presented at international conferences, showcasing his commitment to advancing cutting-edge AI research and practical solutions for global challenges.

Publications

Muhammad Saddam Khokhar, Misbah Ayoub, Zakria, Abdullah Lakhan. (2025). “Advanced Nonlinear Optimization of Low- and High-Resolution Medical Images Using Adaptive Deep Spearman Correlation Analysis (D-SCA) for Pattern Sequence Recognition.” Applied Soft Computing.

Muhammad Saddam Khokhar. (2025). “Energy Harvesting in IoT, Fog, and Blockchain–Thermoelectric Cooling Innovations.”

Muhammad Saddam Khokhar. (2025). “Health Coin: Revolutionizing Global Healthcare with Green Blockchain Technology.”

Zakria Zakria, Jianhua Deng, Rajesh Kumar, Muhammad Saddam Khokhar, Jingye Cai, Jay Kumar. (2022). “Multiscale and Direction Target Detecting in Remote Sensing Images via Modified YOLO-v4.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Abdullah Lakhan, Qurat-ul-ain Mastoi, Mazhar Ali Dootio, Fehaid Alqahtani, Ibrahim R. Alzahrani, Fatmah Baothman, Syed Yaseen Shah, Syed Aziz Shah, Nadeem Anjum, Qammer Hussain Abbasi, et al. (2021). “Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network.” Electronics.

Abdullah Lakhan, Mazhar Ali Dootio, Tor Morten Groenli, Ali Hassan Sodhro, Muhammad Saddam Khokhar. (2021). “Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks.” Electronics.

Conclusion

Dr. Muhammad Saddam Khokhar embodies a dynamic blend of academic rigor, innovative research, and leadership in the field of artificial intelligence. His career reflects a commitment to advancing AI education, developing impactful technologies, and contributing to global scientific knowledge. Through his research, publications, and mentorship, he continues to inspire the next generation of AI professionals while fostering interdisciplinary collaborations that bridge technology with societal advancement.

Qing Zhang | Innovation in Data Analysis | Best Researcher Award

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Prof. Qing Zhang | Innovation in Data Analysis | Best Researcher Award

Sun Yat-sen University, China

PUBLICATION PROFILE

Orcid

INNOVATOR IN DATA ANALYSIS: PROF. QING ZHANG – SUN YAT-SEN UNIVERSITY, CHINA 📊✨

📘 INTRODUCTION

Prof. Qing Zhang, a distinguished scholar from Sun Yat-sen University in China, is a visionary in the field of data analysis and innovation. Renowned for her methodical approach and pioneering techniques, she has significantly advanced the landscape of data-driven research in China and beyond. Her work represents the fusion of mathematical theory and real-world application, making her an influential figure in today’s digital and data-intensive era.

🎓 EARLY ACADEMIC PURSUITS

Prof. Zhang’s academic journey began with a passion for mathematics and computational science. Her foundational education, marked by excellence and curiosity, paved the way for advanced studies in statistical modeling and data interpretation. She pursued rigorous training at top institutions, developing a robust understanding of both theoretical and applied dimensions of data analysis.

🧑‍🏫 PROFESSIONAL ENDEAVORS

Upon joining Sun Yat-sen University, Prof. Zhang quickly emerged as a leading academic voice in the realms of data science and analytics. As a professor and mentor, she has guided numerous students and research teams, establishing a culture of innovation and critical thinking. Her teaching combines technical depth with practical relevance, inspiring the next generation of data analysts and scientists.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Prof. Zhang’s research bridges the gap between algorithmic design and societal needs. Her focus areas include large-scale data mining, predictive analytics, machine learning algorithms, and interdisciplinary data applications. She has contributed to the development of novel methodologies for real-time data processing, high-dimensional statistics, and intelligent systems that address challenges in healthcare, finance, and smart cities.

🌍 IMPACT AND INFLUENCE

Prof. Zhang’s innovations have had wide-reaching effects, not just in academic circles but also in industrial collaborations and government-led data initiatives. Her models and frameworks have been implemented to enhance decision-making processes, improve public health monitoring systems, and support policy formulation with actionable insights. She remains a key contributor to the ongoing digital transformation in China.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

A prolific author, Prof. Zhang has published over 100 peer-reviewed articles in high-impact international journals and conference proceedings. Her work is frequently cited in fields such as artificial intelligence, computational statistics, and systems engineering. She also serves as a reviewer and editorial board member for esteemed journals in data science, reflecting her status as a trusted authority in the field.

🏅 HONORS & AWARDS

Prof. Zhang has received numerous accolades in recognition of her scholarly excellence and innovative contributions. These include national awards for scientific progress, best paper awards from top-tier conferences, and prestigious research grants supporting frontier data science projects. Her leadership is also recognized through invited talks and keynote addresses at major international forums.

🧠 LEGACY AND FUTURE CONTRIBUTIONS

Prof. Zhang’s legacy is defined by her relentless pursuit of knowledge, mentorship, and a commitment to societal advancement through data. She continues to lead cutting-edge research projects while mentoring emerging scholars across China and globally. Looking ahead, she aims to deepen her work in ethical AI, data governance, and sustainable development analytics.

🔔 FINAL NOTE

Prof. Qing Zhang exemplifies excellence in China’s Innovation in Data Analysis. Her academic brilliance, forward-thinking mindset, and tangible impact mark her as a cornerstone in the global data science ecosystem. As the data revolution unfolds, Prof. Zhang stands as a beacon of insight, dedication, and transformation. 🌐💡📈

 📚 TOP NOTES PUBLICATIONS

Title: EGFR‐rich extracellular vesicles derived from highly metastatic nasopharyngeal carcinoma cells accelerate tumour metastasis through PI3K/AKT pathway‐suppressed ROS


Authors: Qing Zhang et al.
Journal: Journal of Extracellular Vesicles
Year: 2020

Title: Dendritic cell biology and its role in tumor immunotherapy

Authors: Qing Zhang et al.
Journal: Journal of Hematology & Oncology
Year: 2020

Title: Melatonin as a Potent and Inducible Endogenous Antioxidant: Synthesis and Metabolism

Authors: Qing Zhang et al.
Journal: Aging-US
Year: 2020

Title: Optimizing Human Epidermal Growth Factor for its Endurance and Specificity Via Directed Evolution: Functional Importance of Leucine at Position 8

Authors: Qing Zhang et al.
Journal: International Journal of Peptide Research and Therapeutics
Year: 2020

Title: Berberine Influences Blood Glucose via Modulating the Gut Microbiome in Grass Carp

Authors: Qing Zhang et al.
Journal: Frontiers in Microbiology
Year: 2019

yayong shi | Bioinformatics | Best Researcher Award

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Assoc Prof Dr. yayong shi | Bioinformatics | Best Researcher Award

Peking University People’s Hospital, China

Publication Profile

Scopus

EARLY ACADEMIC PURSUITS 📚

Dr. Yayong Shi’s academic journey began with a Bachelor’s in Computer Science and Technology from the University of Science and Technology Beijing (2013-2017), where his interest in the intersection of technology and healthcare first took root. His pursuit of a Master’s degree in the same field at the same university (2018-2021) deepened his expertise in computer science, focusing on medical data analysis. This academic foundation laid the groundwork for his joint Ph.D. program, which he undertook between the University of Science and Technology Beijing and the PLA General Hospital Graduate School (2021-2024). His doctoral research marked a pivotal moment in his career, exploring bioinformatics and medical data, and setting him on a path toward blending technology and healthcare for impactful outcomes.

PROFESSIONAL ENDEAVORS 🏥

Dr. Shi’s professional journey led him to serve as an Associate Researcher at Peking University People’s Hospital & National Trauma Medical Center since July 2024. In this role, he is part of groundbreaking work in the medical field, combining computer science with real-time medical applications to drive early disease diagnosis and medical large model development. His position at one of China’s top medical institutions reflects his expertise in medical data processing and his growing reputation in the research community. This role allows him to further his research on multimodal data fusion and its application to early diagnosis, providing valuable insights into improving healthcare delivery and medical outcomes.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Dr. Shi’s research interests revolve around the fusion of multimodal data to enhance early disease diagnosis, particularly in critical medical conditions. His work on Medical Large Models has the potential to revolutionize how data is processed in medical environments, enabling faster and more accurate diagnoses. He is dedicated to improving medical data accuracy and predictive capabilities through advanced machine learning techniques. His contributions also include innovative research on optimizing data imbalances in disease prediction, handling missing labels in electronic health records, and completing medical data features in emergency rescue situations. His work has significantly influenced medical risk identification, offering groundbreaking systems that can process large volumes of healthcare data to identify critical risks in real-time.

IMPACT AND INFLUENCE 🌍

Dr. Shi’s influence extends beyond academic circles into real-world applications, particularly through his involvement in major research projects funded by the National Natural Science Foundation of China and the National Key R&D Program (Precision Medicine). His contributions to the Breast Cancer Onset and Prognosis Tracking System have made strides in precision medicine, where his work is helping shape systems for tracking disease onset and forecasting prognosis. His patents in optimizing medical data handling, especially in irregular medical time-series data and the construction of cross-medical-center chronic disease models, are prime examples of how his research is directly impacting the healthcare sector. Dr. Shi’s innovations are designed to improve efficiency and accuracy in healthcare diagnostics and treatments, offering a global ripple effect in advancing medical technologies.

ACADEMIC CITATIONS 📑

While specific citation counts may not be provided in this text, Dr. Shi’s groundbreaking research in areas such as medical data feature completion and automated discharge monitoring has gained recognition in various academic papers and journals. His work on machine learning and data analysis in healthcare settings has earned citations in studies focused on improving medical technologies, thus contributing to a broader dialogue in the medical technology community.

LEGACY AND FUTURE CONTRIBUTIONS 🌟

Dr. Shi’s legacy in the field of bioinformatics and medical data processing is being shaped by his persistent dedication to enhancing the quality of care through technology. With numerous patents to his name, his innovations are poised to redefine how data is handled in medical contexts. Looking forward, his continued work on medical large models and multimodal data fusion will likely influence the future of precision medicine, further advancing the integration of AI in healthcare. His potential contributions to personalized medicine, where each patient’s treatment is tailored based on data-driven insights, will undoubtedly leave a lasting impact on medical research, care standards, and patient outcomes for generations to come.

IMPORTANT RESEARCH PROJECTS 💡

Dr. Shi has been instrumental in leading major research projects like the Construction and Application of Network Information Support Systems and the Development of Medical Helicopter Systems, both of which aim to improve emergency medical services and infrastructure in China. These projects not only advance his work in medical data processing but also showcase his commitment to improving emergency healthcare systems, potentially saving countless lives by ensuring timely medical interventions.

Publication Top Notes

Node Search Contributions Based Long-Term Follow-Up Specific Individual Searching Model
    • Authors: Shi, Yayong, et al.
    • Journal: Tsinghua Science and Technology
    • Year: 2023
A Disease Transmission Model Based on Individual Cognition
    • Authors: Nian, Fuzhong, Yayong Shi, Zhongkai Dang
    • Journal: International Journal of Modern Physics B
    • Year: 2020
Modeling Information Propagation in High-Order Networks Based on Explicit–Implicit Relationship
    • Authors: Nian, Fuzhong, Yayong Shi, Jun Cao
    • Journal: Journal of Computational Science
    • Year: 2021
EpiRiskNet: Incorporating Graph Structure and Static Data as Prior Knowledge for Improved Time-Series Forecasting
    • Authors: Shi, Yayong, et al.
    • Journal: Applied Intelligence
    • Year: 2024
COVID-19 Propagation Model Based on Economic Development and Interventions
    • Authors: Nian, Fuzhong, Yayong Shi, Jun Cao
    • Journal: Wireless Personal Communications
    • Year: (Year not fully provided, please verify)
COVID-19 Transmission Dynamics in High-Risk Population Networks
    • Authors: Shi, Yayong, et al.
    • Journal: Control Theory and Applications
    • Year: 2020

Mikhail Zabezhaylo | Data Mining | Worldwide Innovation in Research Analytics Award

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Prof Dr. Mikhail Zabezhaylo | Data Mining | Worldwide Innovation in Research Analytics Award

Federal Research Center “Informatics and Management” of the Russian Academy of Sciences | Russia

Author Profile

Orcid

Scopus

Early Academic Pursuits 🎓

Mikhail I. Zabezhaylo, born in 1956, graduated from the Moscow Institute of Physics and Technology (MIPT) in 1979, specializing in Applied Mathematics and Artificial Intelligence (AI). Under the guidance of Prof. D.A. Pospelov and Prof. V.K. Finn, he earned his Ph.D. in Mathematical Cybernetics in 1983 at MIPT, marking the beginning of his deep academic foundation in theoretical computer science.

Professional Endeavors 💼

Dr. Zabezhaylo has held significant positions at major scientific institutions in the USSR and Russia, starting with the All-Union Institute of Scientific and Technical Information (VINITI) and later at the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences (FRC CSC RAS). His career spans roles like Senior Researcher, Associate Professor, and Chief Researcher, and he currently leads the Laboratory “Intelligent Data Analysis”.

Contributions and Research Focus on  Data Mining 🔬

Dr. Zabezhaylo’s research primarily revolves around Artificial Intelligence (AI), data mining, information systems, and decision support systems. He has been involved in high-profile projects with major organizations such as Gazprom, Russian Railroads, and Siemens, focusing on real-world AI applications. His contributions include leading significant R&D projects, like the Skolkovo Foundation’s “Software Defined Networks” mega-grant.

Impact and Influence 🌍

With 180+ scientific publications, Dr. Zabezhaylo has had a major impact on AI and data analysis methodologies, shaping both theoretical and applied computer science. His work is recognized globally, influencing industries, academia, and governmental bodies. His ability to bridge theory and practice has made him a thought leader in AI-powered systems.

Academic Citations 📚

Dr. Zabezhaylo’s work is highly cited, with over 180 publications referenced in major academic journals and conferences. His research on artificial intelligence, decision support systems, and data analysis continues to be a valuable resource for scholars and professionals alike.

Technical Skills 🖥️

Dr. Zabezhaylo is proficient in mathematical modeling, AI, data mining, and decision support systems. His skills extend beyond theory, as he is adept at leading large-scale R&D projects and collaborating with commercial and governmental entities, applying his expertise in real-world solutions.

Teaching Experience 🧑‍🏫

Dr. Zabezhaylo has over 20 years of teaching experience at MIPT, Moscow State University, and other prominent universities. As a professor, he has lectured and conducted seminars on Artificial Intelligence, shaping the future of AI research and training the next generation of AI professionals.

Legacy and Future Contributions 🔮

Dr. Zabezhaylo’s legacy in AI and computer science is firmly established. He continues to lead advancements in data analysis and AI technologies through his work at FRC CSC RAS. His future contributions will likely continue to drive innovation in AI systems and their applications across diverse sectors.

 Notable Publications  📑

On Some Current Myths about Modern Artificial Intelligence

Authors: Zabezhailo, M.I., Mikheyenkova, M.A., Finn, V.K.

Journal: Pattern Recognition and Image Analysis

Year: 2024

On the Problem of Explaining the Results of Intelligent Data Analysis

Authors: Zabezhailo, M.I.

Journal: Pattern Recognition and Image Analysis

Year: 2024

On Some Possibilities of Using AI Methods in the Search for Cause-And-Effect Relationships in Accumulated Empirical Data

Authors: Grusho, A., Grusho, N., Zabezhailo, M., Timonina, E.

Journal: Lecture Notes in Networks and Systems

Year: 2024

Probabilistic Models for Detection of Causal Relationships in Data Sequences

Authors: Grusho, A., Grusho, N., Zabezhailo, M., Timonina, E.

Journal: Lecture Notes in Networks and Systems

Year: 2024

Statistical Causality Analysis

Authors: Grusho, A.A., Grusho, N.A., Zabezhailo, M.I., Samouylov, K.E., Timonina, E.E.

Journal: Discrete and Continuous Models and Applied Computational Science

Year: 2024

Meiying Wu – Healthcare Data Analysis – Best Researcher Award

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Prof. Meiying Wu - Healthcare Data Analysis - Best Researcher Award

Sun Yat-Sen University - China

Author Profile

Early Academic Pursuits

Prof. Meiying Wu's academic journey commenced at Zhengzhou University, China, where she laid the foundation for her scholarly pursuits. Graduating in 2011, she exhibited a keen interest in pharmaceutical sciences, propelling her towards further academic exploration.

Professional Endeavors

Following her undergraduate studies, Wu pursued doctoral research at the prestigious Shanghai Institute of Silicate Technology, Chinese Academy of Sciences. Her doctoral journey culminated in 2016, marking the beginning of her illustrious career in academia. Subsequently, she undertook a pivotal postdoctoral position at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, refining her expertise in drug delivery systems.

Contributions and Research Focus

As a Professor in the School of Pharmaceutical Sciences at the Shenzhen Campus of Sun Yat-sen University, Wu spearheads groundbreaking research in drug delivery systems, with a specialization in bioactive materials and medical applications. Her research endeavors transcend conventional boundaries, delving into the realms of nano biomaterials and nanomedicine. Wu's pioneering work is characterized by a multidimensional approach, encompassing protein expression, cellular homeostasis, and the intricacies of the tissue microenvironment.

Accolades and Recognition

Prof. Wu's contributions to the field have garnered widespread recognition, as evidenced by her numerous accolades. She has been the recipient of esteemed awards such as the National Excellent Youth Fund, Guangdong Outstanding Youth Fund, and Shenzhen Outstanding Youth Fund. Her exceptional achievements have also been acknowledged through prestigious titles, including Top Young Talents of Science and Technology Innovation of the Guangdong Special Support Program and High-level Professional Talents of Shenzhen.

Impact and Influence

Prof. Wu's research has left an indelible mark on the scientific community, evidenced by her extensive publication record and citation index in reputable journals such as Nat. Commun., J. Am. Chem. Soc., and Adv. Mater. Her innovative approach to drug delivery systems has not only expanded the frontiers of knowledge but also holds promise for addressing critical healthcare challenges.

Legacy and Future Contributions

Looking ahead, Meiying Wu remains steadfast in her commitment to advancing the field of pharmaceutical sciences. Her vision encompasses the translation of fundamental research into tangible solutions, with a focus on improving drug delivery efficacy and therapeutic outcomes. As a mentor and Ph.D. supervisor, she continues to inspire the next generation of researchers, fostering a legacy of innovation and excellence in academia.

In conclusion, Meiying Wu's journey from academia to prominence as a distinguished Professor is characterized by unwavering dedication, groundbreaking research, and a relentless pursuit of scientific excellence. Her contributions resonate across disciplines, shaping the landscape of drug delivery systems and positioning her as a trailblazer in the field of pharmaceutical sciences.

Notable Publication

 

Zlatko Kopecki – Innovation in Data Analysis – Best Researcher Award 

Published on by Research Data Analysis

Dr. Zlatko Kopecki - Innovation in Data Analysis - Best Researcher Award 

University of South Australia - Australia

Author Profile

Early Academic Pursuits

Dr. Zlatko Kopecki's academic journey began with his role as a Technical Officer in Histopathology at Clinpath Laboratories from 2003 to 2005, followed by a position as a Medical Scientist in Histopathology at Adelaide Pathology Partners from 2005 to 2011. During this period, he honed his skills in laboratory medicine, culminating in earning the Terumo Prize for Excellence in Laboratory Medicine with Honours from the University of South Australia (UniSA) in 2007. His dedication to his field was further recognized with a Dean’s Commendation for the quality of his Ph.D. thesis at the University of Adelaide in 2011.

Professional Endeavors

Dr. Kopecki's professional career is marked by several notable appointments. From 2010 to 2012, he served as a Research Officer at the Women’s and Children’s Hospital, where he began to establish his research credentials. His trajectory continued with a National Health and Medical Research Council (NHMRC) Early Career Researcher (ECR) Fellowship at UniSA from 2012 to 2015, during which he also held an honorary research fellowship at Queen Mary University of London. He progressed to the role of Senior Research Fellow at UniSA's Future Industries Institute (FII) from 2015 to 2021. His international engagements included visiting research fellowships at the University of Freiburg (2010), University of Lübeck (2017), and the University of Bath (2020).

Contributions and Research Focus

Dr. Kopecki's research has consistently focused on innovative approaches to wound management and therapy for rare skin diseases, particularly Epidermolysis Bullosa (EB). He has pioneered the development of biofilm-disrupting technologies and stimuli-responsive wound dressings, as well as antimicrobial photodynamic therapy (aPDT). His work also includes the development of antiseptic wound cleansers, medicated hydrogels, and antimicrobial materials for treating infections. His research employs various animal models to answer critical questions about wound infection and skin diseases, contributing significantly to product development and commercialization pathways.

Accolades and Recognition

Dr. Kopecki's contributions to research and patient advocacy have been recognized with numerous awards. Notable among these are the Young Investigator of the Year Award from the Australasian Wound & Tissue Repair Society (AWTRS) in 2016 and the Tall Poppy Award for outstanding scientific achievements in South Australia in 2017. His innovative research has also earned him prestigious grants, including multiple NHMRC Ideas Grants and the Alexander von Humboldt Fellowship for Experienced Researchers (2024-2026).

Impact and Influence

Dr. Kopecki's influence extends beyond his research to impactful patient advocacy. Since 2009, he has been actively involved with DEBRA (an international patient support organization for those affected by EB), where he has held various leadership positions. His efforts have led to significant initiatives, such as the National EB Dressing Scheme in Australia and the In Home Nurse Program, which have greatly improved patient care. His work with DEBRA International during the Ukrainian conflict highlights his commitment to global patient advocacy, providing essential support to EB patients affected by the war.

Legacy and Future Contributions

Dr. Kopecki's legacy is marked by his dedication to improving the lives of those with rare skin diseases through both research and advocacy. His innovative approaches in developing new therapies and his active role in patient support programs have set new standards in the field. Looking forward, Dr. Kopecki aims to continue his pioneering research, focusing on translating his findings into clinical practice to benefit patients worldwide. His ongoing collaborations with industry partners and his involvement in global patient advocacy programs ensure that his work will continue to have a significant impact on the field of wound management and rare skin diseases.

Citations

A total of 1592 citations for his publications, demonstrating the impact and recognition of her research within the academic community.

  • Citations   1592
  • h-index      24
  • i10-index    42

Notable Publication