Mr. Saurabh Pahune | Generative AI | Best Researcher Award

Mr. Saurabh Pahune | Generative AI | Best Researcher Award

Techncial Architect, Cardinal health, Ohio, United States

Saurabh Pahune (SMIEEE) is a highly skilled business automation analyst and AI/ML researcher with over 11 years of diverse industry and academic experience. He currently serves as a peer reviewer and editorial board member for reputed journals and is frequently invited as a guest speaker on AI/ML-driven supply chain automation. Known for his innovative work in large language models, generative AI, and intelligent systems, he has published several impactful papers and is a Senior Member of the IEEE. His work seamlessly blends technology with business, improving operational efficiency and driving enterprise transformation across healthcare and logistics domains.

Publication Profile

Google Scholar

ORCID

Scopus

🎓 Education Background

Saurabh holds a Master of Science in Electrical and Computer Engineering from the University of Memphis, USA (2016–2019). He earned his M.Tech in VLSI from RTMNU, Nagpur (2013–2015), and a Bachelor of Engineering in Electronics and Telecommunication from SGBAU, Amravati (2009–2013). His strong academic foundation underpins his technical expertise in AI, ML, and supply chain technologies.

💼 Professional Experience

Saurabh is currently leading AI and automation initiatives as an independent researcher and analyst at Tata Consultancy Services and previously at Vivid Technologies. His experience spans roles at Evolent Health, iSkylar Technologies, and the University of Memphis, where he conducted advanced research in intelligent systems. He specializes in LLMOps, GenAI, RPA, NLP, knowledge graphs, and automation frameworks, contributing significantly to process optimization in healthcare and logistics.

🏆 Awards and Honors

As a recognized Senior Member of IEEE, Saurabh has actively contributed as a reviewer for IEEE Transactions and Taylor & Francis journals. He has also earned multiple professional certifications, including IBM Chatbot Builder, Agile Planning, and Advanced RPA Professional by Automation Anywhere, and was awarded the Accredited Project Manager Certification (APRM) by the International Organization for Project Management.

🔬 Research Focus

Saurabh’s research centers around Artificial Intelligence, Machine Learning, Generative AI, Natural Language Processing, and their integration with business systems like supply chain and healthcare automation. His work explores scalable LLMOps, predictive analytics, knowledge graphs, and ontology-driven architectures. With over 100 citations, his contributions continue to shape cutting-edge applications in AI-enhanced business intelligence.

🔚 Conclusion

Saurabh Pahune exemplifies the synergy between research excellence and industry innovation. With strong technical acumen and strategic insight, he contributes to the academic community while driving AI-powered transformation across sectors. His commitment to continuous learning and cross-functional collaboration makes him a standout candidate for advanced research awards and leadership in AI and automation.

📚 Top Publications –Mr. Saurabh Pahune

  1. Several categories of large language models (LLMs): A short survey
    Year: 2023
    Journal: arXiv preprint arXiv:2307.10188
    Cited by: 36
    Co-author(s): M. Chandrasekharan

  2. Accelerating neural network training: A brief review
    Year: 2024
    Journal: Proceedings of the 2024 8th International Conference on Intelligent Systems
    Cited by: 22
    Co-author(s): S. Nokhwal, P. Chilakalapudi, P. Donekal, S. Nokhwal

  3. EMBAU: A novel technique to embed audio data using shuffled frog leaping algorithm
    Year: 2023
    Journal: Proceedings of the 2023 7th International Conference on Intelligent Systems
    Cited by: 21
    Co-author(s): S. Nokhwal, A. Chaudhary

  4. Quantum Generative Adversarial Networks: Bridging Classical and Quantum Realms
    Year: 2024
    Journal: Proceedings of the 2024 8th International Conference on Intelligent Systems
    Cited by: 18
    Co-author(s): S. Nokhwal, A. Chaudhary

  5. Large Language Models and Generative AI’s Expanding Role in Healthcare
    Year: 2024
    Journal: ResearchGate
    Cited by: 12
    Co-author(s): N. Rewatkar

  6. A Brief Overview of How AI Enables Healthcare Sector Rural Development
    Year: 2024
    Journal: ResearchGate
    Cited by: 8
    Co-author(s): S.A. Pahune

  7. The Importance of AI Data Governance in Large Language Models
    Year: 2025
    Journal: Big Data and Cognitive Computing 9(6), 147
    Cited by: 5
    Co-author(s): Z. Akhtar, V. Mandapati, K. Siddique

  8. Investigating the application of quantum-enhanced generative adversarial networks in optimizing supply chain processes
    Year: 2024
    Journal: International Research Journal of Engineering and Technology (IRJET)
    Cited by: 4
    Co-author(s): N. Rewatkar

  9. Cognitive automation in the supply chain: Unleashing the power of RPA vs. GenAI
    Year: 2024
    Journal: ResearchGate
    Cited by: 4
    Co-author(s): N. Rewatkar

  10. Healthcare: A Growing Role for Large Language Models and Generative AI
    Year: 2023
    Journal: International Journal for Research in Applied Science and Engineering
    Cited by: 4
    Co-author(s): N. Rewatkar

 

Dongbeom Kim | Artificial Intelligence | Best Researcher Award

Mr. Dongbeom Kim | Artificial Intelligence | Best Researcher Award

Master’s Student, University of Seoul, South Korea

Dongbeom Kim is a dedicated Master’s student at the University of Seoul, specializing in Geoinformatics under the mentorship of Professor Chulmin Jun. With a robust academic background in Geography and a passion for innovative research, Dongbeom is actively engaged in developing smart systems for urban planning and vehicle safety. His work spans advanced studies in fire evacuation simulations, the application of artificial intelligence in urban growth modeling, and the development of safe driving systems for two-wheeled vehicles. 📊🛵

Publication Profile

Strengths for the Award:

  1. Academic Background: Dongbeom Kim has a solid educational foundation in Geography and Geoinformatics, with high GPAs in both his undergraduate and current Master’s studies. His ongoing education in Geoinformatics at the University of Seoul under the guidance of a reputed advisor further strengthens his research credentials.
  2. Research Publications: He has authored several papers published in reputable SCIE/ESCI journals like Sensors and Applied Sciences, along with multiple domestic publications. His research spans various topics, including fire evacuation simulations, vehicle safety, and urban growth modeling, indicating a diverse research portfolio.
  3. Conferences and Presentations: Dongbeom Kim has actively presented his research at several international and national conferences, such as the 18th International Conference on Location Based Services in Belgium and the Korean Society for Geospatial Information Science. These experiences highlight his engagement with the academic community and his ability to communicate his research effectively.
  4. Patents and Innovation: He is a co-inventor on four patents related to vehicle safety and route generation, demonstrating innovation and practical application of his research.
  5. Research Projects: Participation in multiple research projects, including those focused on greenhouse gas emission reduction and environmental big data analysis, shows his capability to contribute to significant scientific endeavors.

Areas for Improvement:

  1. Research Leadership: While Dongbeom Kim has collaborated on numerous projects and publications, there is limited evidence of him taking on a leading role in these efforts. Demonstrating more leadership in research projects or publications could strengthen his profile.
  2. Diversity in Research Impact: Although his research covers a range of topics, the majority are closely related to vehicle safety and geospatial data analysis. Expanding his research to cover other areas of geoinformatics or interdisciplinary applications could enhance the breadth of his research impact.
  3. Published Impact Factor: As some of his research is still under review and the impact factors of the journals in which he has published are not mentioned, highlighting the impact factor or citation index of his published work could further substantiate his research quality.

 

Education

Dongbeom holds a Bachelor’s degree in Geography from Kongju National University (2015-2021), achieving a GPA of 3.9/4.5. He is currently pursuing a Master’s degree in Geoinformatics at the University of Seoul, where he has achieved an impressive GPA of 4.33/4.5. 🎓🌍

Experience

Dongbeom’s experience includes multiple research projects, focusing on geospatial information science, urban growth modeling, and traffic safety. He has contributed to several conferences and published numerous peer-reviewed articles in international journals. His practical skills are reinforced by his active involvement in projects such as the development of a good driving evaluation system for two-wheeled vehicles and environmental big data analysis. 🌐📝

Research Focus

Dongbeom’s research primarily revolves around geoinformatics, fire evacuation simulations, urban growth modeling, and traffic safety. He is particularly interested in utilizing sensor-based approaches and artificial intelligence techniques to address urban challenges and enhance public safety. 🚒🌆

Awards and Honors

Dongbeom has presented his work at prestigious international and domestic conferences and has collaborated on innovative projects that have received national attention. He is also recognized for his contributions to patents related to traffic safety and environmental management. 🏆🔬

Publication Top Notes

Under Review: Dongbeom Kim, Hyemin Kim, Yuhan Han, Chulmin Jun, “Fire Evacuation Simulation with Agent-Based Fire Recognition Propagation” (Physica Scripta, 2024)

Dongbeom Kim, Hyemin Kim, Suyun Lee, Qyoung Lee, Minwoo Lee, Jooyoung Lee, Chulmin Jun, “Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System” (Sensors, 2024) – Cited by 2 articles

Dongbeom Kim, Hyemin Kim, Chulmin Jun, “The Detection of Aggressive Driving Patterns in Two-Wheeled Vehicles Using Sensor-Based Approaches” (Applied Sciences, 2023) – Cited by 3 articles

Minjun Kim, Dongbeom Kim, Daeyoung Jin, Geunhan Kim, “Application of Explainable Artificial Intelligence (XAI) in Urban Growth Modeling: A Case Study of Seoul Metropolitan Area, Korea” (Land, 2023) – Cited by 5 articles

Suyun Lee, Dongbeom Kim, Chulmin Jun, “Calculation of Dangerous Driving Index for Two-Wheeled Vehicles Using the Analytic Hierarchy Process” (Applied Sciences, 2023) – Cited by 1 article

Minjun Kim, Dongbeom Kim, Geunhan Kim, “Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea” (International Journal of Environmental Research and Public Health, 2022) – Cited by 4 articles 📖🔗

Conclusion:

Dongbeom Kim appears to be a promising candidate for the “Best Researcher Award” due to his solid academic background, active research publication record, involvement in innovative patents, and participation in impactful research projects. To further strengthen his candidacy, he could focus on assuming leadership roles in his research, diversifying his research impact, and emphasizing the citation metrics of his work. Overall, his contributions to the field of geoinformatics and vehicle safety suggest he is a strong contender for this award.