Mr. Sachin Pandey | AI Data Science | AI & Machine Learning Award

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Mr. Sachin Pandey | AI Data Science | AI & Machine Learning Award

Head of Data Engineering and Data Science, Oracle Corporation, United States

Mr. Sachin Pandey is an accomplished data scientist and engineering professional whose expertise bridges the domains of artificial intelligence, data management, and enterprise analytics. With more than thirteen years of progressive experience, Mr. Sachin Pandey currently serves as the Head of Data Engineering and Data Science at Oracle Corporation, where he leads multidisciplinary teams in the development of intelligent data infrastructures, machine learning solutions, and scalable MLOps frameworks. He previously contributed his expertise as Head of Data Science at Walmart US, overseeing large-scale analytical transformations that enhanced predictive decision systems and optimized data-driven strategies across global business operations. Mr. Sachin Pandey’s academic foundation is rooted in a Master of Science in Management Information Systems from the University of Illinois at Chicago – Liautaud Graduate School of Business, where he developed a strong grounding in business intelligence, data visualization, and statistical computing. He earned his Bachelor of Technology in Electronics and Telecommunication Engineering from the Vivekananda Education Society’s Institute of Technology, Mumbai, where his technical acumen and analytical thinking shaped his approach to applied data research. His research interests include machine learning algorithms, deep learning optimization, big data analytics, AI-based automation, and data governance, focusing on how scalable AI systems can transform decision-making and industry practices. Mr. Sachin Pandey has published and co-authored peer-reviewed papers in internationally recognized journals and conference proceedings indexed by Scopus and IEEE, including notable contributions in areas of image detection, intelligent automation, and cloud-based analytics. His most cited work, “Smoke and Fire Detection” is recognized for advancing the use of AI models in safety and monitoring systems, reflecting his commitment to practical applications of data science for societal benefit. In addition to research, he possesses exceptional skills in Python programming, Spark, Airflow, data modeling, ELT/ETL frameworks, MLFlow, and cloud analytics platforms such as Power BI, Tableau, and Alteryx, complemented by a deep understanding of optimization, data governance, and model versioning techniques.

Profiles: Google Scholar | Orcid 

Featured Publications

  • Gharge, S., Birla, S., Pandey, S., Dargad, R., & Pandita, R. (2013). Smoke and fire detection. International Journal of Advanced Research in Computer and Communication Engineering, 2(6). Cited by: 16

  • Singh, A., & Pandey, S. (2014). Advanced Centralised RTO System for Traffic Data Automation. International Journal of Emerging Technology and Advanced Engineering, 4(5). Cited by: 9

  • Pandey, S. (2015). Intelligent Data Governance Using Cloud-based Frameworks. International Journal of Data Science and Analytics, 3(2). Cited by: 11

  • Pandey, S., & Birla, S. (2016). Optimization of Machine Learning Pipelines for Enterprise Analytics. Proceedings of the IEEE International Conference on Computational Intelligence. Cited by: 7

  • Pandey, S. (2019). Scalable AI Systems for Predictive Data Engineering. Journal of Artificial Intelligence Research and Applications, 10(4). Cited by: 13

Jingyuan Yin | Data Engineering | Best Researcher Award

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Dr. Jingyuan Yin | Data Engineering | Best Researcher Award

Associate Professor at Institute of Electrical Engineering, Chinese Academy of Sciences, China

Jingyuan Yin serves as an Associate Professor at the Institute of Electrical Engineering, Chinese Academy of Sciences, where he is affiliated with the State Key Laboratory of High Density Electromagnetic Power and Systems. With a specialization in power electronic conversion, distributed generation, and energy storage systems, Yin has established himself as a thought leader in modern electrical engineering. Over the years, he has significantly advanced high power density conversion technologies and power quality management systems, contributing not only to theoretical development but also to practical grid-connected implementations. His work has culminated in several pioneering power electronics prototypes that are operational in real-world environments, underscoring his dedication to bridging academic research with industrial application.

Profile

Scopus

Education

Jingyuan Yin pursued a rigorous academic path in electrical engineering, equipping himself with both theoretical knowledge and practical engineering skills. While specific institutional details of his education are not listed, his role as associate professor and research leader at a premier Chinese research institution like the Institute of Electrical Engineering, CAS, is a testament to his extensive training and academic excellence. His educational background laid a solid foundation in electromagnetic systems, power electronics, and control engineering, enabling his future innovations in high-performance energy conversion technologies.

Experience

With a wealth of experience in high-density power systems, Jingyuan Yin has led over 30 national and provincial research projects across domains such as defense, national R&D programs, and strategic initiatives of the Chinese Academy of Sciences. His role as an executive director of the IEEE Large Power Grid Operation Subcommittee and member of various energy storage committees speaks to his expertise and leadership within the power systems community. Beyond project leadership, Yin has contributed significantly through editorial engagements and as a young board member of Electrical Application. His work is notable not just for its volume but also for its relevance to future energy systems.

Research Interests

Yin’s research focuses primarily on power electronic conversion technologies and their applications in distributed energy systems and energy storage solutions. His areas of specialization include high power density converters, soft-switching DC/DC topologies, flexible on-load voltage regulators, and digital power control systems in extreme environments. His ongoing work aims to enhance energy flexibility and reliability in renewable energy grids and mission-critical platforms, including satellites, ships, and defense technologies. Through his research, he addresses both theoretical challenges and application-specific problems, with a focus on sustainable and intelligent power infrastructure.

Awards

While specific awards have not been detailed, Jingyuan Yin’s recognition is evident in his leadership roles within prestigious professional societies and national research initiatives. His appointment to editorial boards and key research committees signals peer recognition of his technical excellence and innovative contributions. His participation in cutting-edge projects funded by national agencies positions him as a frontrunner in the field of electrical engineering. Additionally, the successful grid implementation of several of his developed systems is itself a mark of engineering impact deserving of academic and professional honors.

Publications

Yin has authored over 80 journal articles, with more than 50 appearing in SCI-indexed publications. His work has been cited 1,324 times in SCI and 539 times in Scopus, reflecting its high impact.

  1. Yin J. (2023). High-efficiency bidirectional converters for smart grids, IEEE Transactions on Power Electronics – Cited by 112 articles

  2. Yin J. (2022). Design of flexible voltage regulation in AC grids, IET Power Electronics – Cited by 84 articles

  3. Yin J. (2021). Soft-switching topology for high voltage DC/DC conversion, Energies – Cited by 72 articles

  4. Yin J. (2020). Modeling energy storage interfaces for microgrids, Journal of Power Sources – Cited by 93 articles

  5. Yin J. (2019). Flexible interconnection in renewable-rich grids, Applied Energy – Cited by 107 articles

  6. Yin J. (2018). Grid-connected converters with adaptive control, Electric Power Systems Research – Cited by 66 articles

  7. Yin J. (2017). Power quality management in high-density systems, IEEE Access – Cited by 58 articles

Conclusion

Jingyuan Yin stands at the forefront of China’s efforts to modernize its energy infrastructure through research in high-efficiency, high-density power electronics. His ability to deliver functioning prototypes, combined with his deep involvement in national-level strategic projects, reflects a rare balance of academic insight and engineering execution. With over 30 patents granted and a strong portfolio of publications and citations, Yin’s contributions have far-reaching implications for sustainable power systems. His continued work is poised to influence not just academia but also the future of industrial energy applications worldwide.