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

 

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Doctoral student, University of Science and Technology Beijing, China

Ai-Ai Wang is a passionate and dedicated young researcher born in March 1998 in Langfang, Hebei Province, China. A proud member of the Communist Party of China (CPC), she is currently based at the University of Science and Technology Beijing (USTB), where she serves as the Secretary of the 16th Party Branch, 4 Zhaizhai. With a solid academic foundation in mining and civil engineering, Ai-Ai has excelled in both academic and research spheres, contributing significantly to digital and intelligent mining technologies. Her work emphasizes physical dynamics in tailings sand cementation and filling, showing strong potential for innovation in sustainable mining practices.

Publication Profile

Scopus

🎓Education Background:

Ai-Ai Wang completed her Bachelor of Science in Mining Engineering from North China University of Science and Technology in 2021. She further pursued her Master’s degree in Civil Engineering at the University of Science and Technology Beijing (2021.09–2024.06), affiliated with the School of Civil and Resource Engineering.

🛠️Professional Experience:

Alongside her academic journey, Ai-Ai has undertaken significant responsibilities, currently serving as Secretary of the Party Branch at USTB. Her leadership extends beyond administration into collaborative research projects, software development, and patent contributions under renowned mentors such as Prof. Cao Shuai. She has played vital roles in developing intelligent systems for mining operations, reinforcing her multidisciplinary strengths.

🏅Awards and Honors:

Ai-Ai Wang has been recognized extensively for her academic and research excellence. Notable accolades include the “Top Ten Academic Stars” at USTB (2023), a National Scholarship for Master’s Degree Students (2022), the prestigious Taishan Iron and Steel Scholarship (2023), and multiple First-Class Academic Scholarships from USTB. She was twice named an Outstanding Three-Good Graduate Student and honored by her school as an outstanding individual. Moreover, she has received scientific awards such as the First Prize from the China Gold Association and the Second Prize from the China Nonferrous Metals Industry for her impactful contributions to green and safe mining.

🔬Research Focus:

Ai-Ai Wang’s research is rooted in advanced techniques of tailings sand cementation, intelligent filling systems, and digital mining. She explores the structural stability of backfills, application of nanomaterials, and CT-based 3D modeling of internal structures. Her work blends civil engineering, environmental safety, and digital innovation, aiming to enhance sustainability and efficiency in modern mining. She also contributes to cutting-edge software systems and patented technologies for mining design and operation support.

📝Conclusion:

Ai-Ai Wang stands out as a promising engineer and researcher whose academic achievements, professional dedication, and innovative research in intelligent mining set a high standard for future civil and mining engineers. Her trajectory reflects not just technical mastery but a deep commitment to sustainable and smart engineering solutions in the mining industry.

📚Top Publications with Details

Effect of height to diameter ratio on dynamic characteristics of cemented tailings backfills with fiber reinforcement through impact loading – Construction and Building Materials, 2022
Cited by: 26 articles
Influence of types and contents of nano cellulose materials as reinforcement on stability performance of cementitious tailings backfill – Construction and Building Materials, 2022
Cited by: 20 articles
Quantitative analysis of pore characteristics of nanocellulose reinforced cementitious tailings fills using 3D reconstruction of CT images – Journal of Materials Research and Technology, 2023
Cited by: 12 articles

 

Young-Chan Lee | Generative AI | Excellence in Research

Prof. Young-Chan Lee | Generative AI | Excellence in Research

Professor, Dongguk University, South Korea

🌟 Dr. Young-Chan Lee is a distinguished professor at Dongguk University, Korea, where he has been serving since 2004. With a rich academic and leadership background, he also holds key roles such as Dean of the Continuing Education Institute and the Institute of Ecology Education. Dr. Lee’s contributions extend globally, including positions at universities in Vietnam and Malaysia. His dedication to information systems and management science has earned him a stellar reputation in both academia and industry.

Publication Profile

ORCID

Education

🎓 Dr. Lee completed his Ph.D. in Management Science from Sogang University in 2003, specializing in data mining, system dynamics, and e-commerce strategy. He also holds an M.A. in Management Science from the same institution, where he concentrated on multi-objective decision-making models, and a B.A. in Business Administration with a focus on finance, econometrics, and management science.

Experience

💼 Over his career, Dr. Lee has taken on leadership roles at Dongguk University, including Dean of the School of Business Administration and Office of International Affairs. He has also worked internationally as an Adjunct Professor at Ton Duc Thang University in Vietnam and as a Senior Researcher at INTI International University in Malaysia. His academic career is complemented by editorial roles in several prestigious journals.

Research Focus

🔬 Dr. Lee’s research interests lie in data mining, machine learning for business analytics, knowledge management, system dynamics, and fintech innovation. He is particularly known for applying systems thinking and multi-criteria decision-making to tackle complex business and management challenges.

Awards and Honours

🏆 Dr. Lee has received numerous accolades, including multiple Best Paper Awards from leading associations such as the Korea Association of Information Systems. His work has also earned recognition on a global scale, including the Most Cited Paper Award from Elsevier and the Top Downloaded Paper Award from Wiley.

Publication Top Notes

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives

Ethical AI in Financial Inclusion: The Role of Algorithmic Fairness on User Satisfaction and Recommendation

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes through SDL and AIDUA Perspectives