Boris Genin | Data Engineering | Best Researcher Award

Best Researcher Award

Boris Genin
Federal Institute of Industrial Property

Boris Genin
Affiliation Federal Institute of Industrial Property
Country Russia
Scopus ID 57222040159
Documents 3
Citations 3
h-index 1
Subject Area Data Engineering
Event International AI Data Scientists Award
ORCID 0000-0003-3514-1340

Boris Genin of the Federal Institute of Industrial Property has demonstrated academic engagement in the field of Data Engineering through scholarly publications, intellectual property research, and contributions to technology-driven information systems. His research profile reflects participation in scientific activities that support data management, innovation assessment, and digital transformation initiatives.[1]

Abstract

This article highlights the academic profile of Boris Genin and his relevance to the Best Researcher Award. His work focuses on data-related research activities, innovation systems, and intellectual property information management. Through scholarly publications and participation in scientific research, he has contributed to knowledge development within Data Engineering and associated digital domains.[1]

Keywords

Data Engineering, Research Innovation, Information Systems, Intellectual Property Analytics, Digital Transformation, Data Management, Scientific Research.

Introduction

Research excellence is measured through scholarly productivity, knowledge dissemination, and contributions to professional practice. Boris Genin’s academic record reflects engagement with data-centric methodologies and research activities that support innovation management and information processing. His published work contributes to ongoing discussions regarding efficient data utilization and technology-enabled decision-making processes.[2]

Research Profile

Affiliated with the Federal Institute of Industrial Property, Boris Genin has developed a research portfolio connected to data engineering applications and intellectual property information systems. His Scopus profile records multiple indexed publications and citations, reflecting active participation within scholarly communication networks.[1]

Research Contributions

His contributions include research supporting information analysis, structured data organization, and innovation-related knowledge systems. Such work helps strengthen evidence-based decision processes and supports the broader objectives of data-driven research environments.[3]

Publications

  • Indexed scholarly publications related to data engineering and information management.
  • Research outputs contributing to innovation analytics and digital information systems.
  • Works cited within academic databases and research platforms.

Research Impact

Although at an early citation stage, the documented impact of the researcher’s publications demonstrates visibility within the academic community. Citation records and indexing within international databases indicate engagement with global scholarly audiences and ongoing relevance within specialized research areas.[1]

Award Suitability

Boris Genin’s scholarly activities align with the objectives of the International AI Data Scientists Award. His contributions to data engineering, research dissemination, and innovation-focused information systems support the criteria commonly associated with academic recognition programs. The combination of publications, citations, and institutional affiliation provides a foundation for consideration under the Best Researcher Award category.[1]

Conclusion

Boris Genin represents an example of a researcher contributing to data engineering and innovation-related scholarship. His academic profile reflects engagement with research, publication, and knowledge dissemination activities that support scientific advancement. These achievements establish a suitable basis for recognition through the Best Researcher Award program.

References

  1. Elsevier. (n.d.). Scopus author details: Boris Genin, Author ID 57222040159. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57222040159
  2. ORCID. (n.d.). Research profile of Boris Genin.
    https://orcid.org/0000-0003-3514-1340
  3. Digital Object Identifier Foundation. (n.d.). DOI reference resource.
    https://doi.org/10.1016/j.procs.2021.05.001

Tianying Chang | Data Engineering | Research Excellence Award

Prof. Tianying Chang | Data Engineering | Research Excellence Award

Professor | Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences | China

Tianying Chang focuses on optical sensing, fiber optic systems, and terahertz spectroscopy. Their research advances high-sensitivity measurement techniques, distributed acoustic sensing, and signal processing methods. With strong contributions to instrumentation and photonics, they develop innovative models and algorithms for real-time monitoring, detection, and analysis in engineering and applied physics domains.

Citation Metrics (Scopus)

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Citations
2361

Documents
162

h-index
29


View Scopus Profile

Featured Publications

Phase Correction Based on Adaptive Fading Feedback in Distributed Fiber Acoustic Sensing Systems
– IEEE Transactions on Instrumentation and Measurement, 2025 | Citations: 1

Terahertz spectroscopy studies on dielectric and thermal stability properties of polymer resins
– Journal of the Optical Society of America B, 2025 

Distributed Fiber Optic Acoustic Sensing System Based on Fading Mask Autoencoder and Application in Water Navigation Security Events Identification
– Acta Photonica Sinica, 2025 

Tunnel damage detection based on finite element simulation and optical fiber sensing
– Infrared and Laser Engineering, 2024 | Citations: 2

Accurate detection of neotame hydrates and their transformation using terahertz spectroscopy
– Infrared Physics and Technology, 2024 | Citations: 2

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

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