Vijay Sangolgi | Deep Learning | Young Researcher Award

Published-on by Indian Scientist Awards

Young Researcher Award

Vijay Sangolgi
Affiliation N. K. Orchid College of Engineering & Technology, Solapur
Country India
Scopus ID 58843968000
Documents 16
Citations 10
h-index 2
Subject Area Deep Learning
Event Indian Scientist Awards
ORCID 0009-0004-9219-8006

Vijay Sangolgi

N. K. Orchid College of Engineering & Technology, Solapur,

 

Vijay Sangolgi is affiliated with N. K. Orchid College of Engineering & Technology, Solapur, India. His scholarly activities are associated with the field of Deep Learning, where he has contributed to emerging computational methodologies, intelligent systems, and applied artificial intelligence research. Through academic publications and research dissemination, he has established a growing presence within the scientific community and demonstrates the characteristics commonly recognized under young researcher excellence initiatives.[1]

Abstract

The Young Researcher Award recognizes emerging scholars demonstrating research productivity, academic engagement, and contributions to advancing knowledge within their respective disciplines. Vijay Sangolgi’s academic profile reflects involvement in Deep Learning research, supported by peer-reviewed publications, scholarly dissemination, and measurable citation activity. The combination of publication output, interdisciplinary relevance, and commitment to technological advancement provides a basis for consideration within research recognition frameworks focused on early-career achievement.[1][2]

Keywords

Deep Learning; Artificial Intelligence; Machine Learning; Neural Networks; Computational Intelligence; Research Excellence; Emerging Scholar; Scientific Publications; Knowledge Discovery; Young Researcher Award.

Introduction

Research recognition programs play an important role in encouraging innovation, scientific inquiry, and knowledge dissemination across academic disciplines. The Young Researcher Award category is designed to acknowledge researchers who demonstrate notable scholarly activity during the early stages of their academic careers. Within the rapidly evolving field of Deep Learning, contributions involving predictive modeling, intelligent systems, and data-driven decision making continue to influence both theoretical and practical advancements.[2]

Research Profile

Vijay Sangolgi is associated with N. K. Orchid College of Engineering & Technology, Solapur, India. His documented scholarly record includes sixteen indexed documents, ten citations, and an h-index of two according to available research metrics. His academic interests are centered on Deep Learning and related computational methodologies that support intelligent automation and advanced analytical systems.[1]

  • Research specialization in Deep Learning and Artificial Intelligence.
  • Participation in scholarly publication and dissemination activities.
  • Contribution to computational and intelligent system research.
  • Engagement with interdisciplinary technological applications.

Research Contributions

The research activities attributed to Vijay Sangolgi are aligned with contemporary developments in machine learning and Deep Learning technologies. Such work contributes to the broader objective of improving computational efficiency, predictive accuracy, and intelligent decision-support systems. The field continues to generate significant academic and industrial interest due to its applications in healthcare, engineering, business analytics, and automation.[3]

  • Application of machine learning methodologies to complex datasets.
  • Exploration of intelligent computational models.
  • Support for innovation through algorithmic research.
  • Contribution to academic knowledge exchange and scholarly communication.

Publications

The publication record associated with the researcher reflects sustained scholarly engagement. Indexed publications contribute to scientific visibility, facilitate peer evaluation, and promote the dissemination of research findings across the academic community.[1]

  1. Peer-reviewed journal articles in Deep Learning and related technologies.
  2. Conference proceedings and technical research presentations.
  3. Collaborative publications supporting interdisciplinary research.
  4. Scholarly outputs contributing to emerging AI applications.

Research Impact

Research impact may be evaluated through publication output, citation performance, academic visibility, and contribution to ongoing scientific dialogue. The documented citation record demonstrates that the research outputs have received scholarly attention and contribute to the broader exchange of scientific knowledge. Continued publication activity has the potential to expand influence across academic and applied research domains.[1]

Award Suitability

The Young Researcher Award emphasizes research promise, scholarly productivity, innovation, and contribution to scientific advancement. Based on available academic indicators, Vijay Sangolgi demonstrates characteristics associated with emerging research excellence, including publication activity, engagement with contemporary technological research, and participation in scholarly communication. These factors support consideration within award programs recognizing early-career academic achievement.[1][4]

Conclusion

Vijay Sangolgi’s academic profile reflects ongoing engagement with Deep Learning research and scholarly publication activities. Through contributions to scientific literature and participation in advancing computational intelligence methodologies, the researcher represents the type of emerging scholar frequently recognized by early-career research distinction programs. The Young Researcher Award serves as a platform for acknowledging such contributions and encouraging future scientific achievement.[1]

References

  1. Scopus author details: Vijay Sangolgi, Author ID 58843968000. Scopus. https://www.scopus.com/authid/detail.uri?authorId=58843968000
  2. Facial recognition enhanced music recommendation system: An exploration of CNN in user centric music discovery
    https://pubs.aip.org/aip/acp/article-abstract/3385/1/030001/3380727/Facial-recognition-enhanced-music-recommendation?redirectedFrom=fulltext
  3. Artificial Intelligence and Emerging Technology (AI Summit), Global AI Summit – International Conference on. https://ieeexplore.ieee.org/xpl/conhome/11410557/proceeding
  4. Revolutionizing Fake News Detection with Artificial Neural Networks and Recurrent Neural Networks. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5091615

S.S.Subashka Ramesh | Medicinal Chemistry | Best Researcher Award-duplicate-1

Published-on by Indian Scientist Awards

Dr. S.S. Subashka Ramesh | Data Science and Machine learning | Best Researcher Award

SRM Institute of Science and Technology india, India

Dr. S.S. Subashka Ramesh is an accomplished academic and researcher in Computer Science and Engineering with a strong foundation in advanced computing and data-driven technologies. Holding doctoral and postgraduate qualifications, she has extensive teaching and research experience, mentoring scholars and contributing to impactful innovations. Her research interests include machine learning, artificial intelligence, edge computing, and medical imaging. With notable publications, patents, and academic leadership, she has earned professional recognition and continues to advance knowledge through research, collaboration, and technology-driven solutions for real-world challenges.

Citation Metrics (Google Scholar)

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Featured Publications

Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

Published-on by Indian Scientist Awards

Dr. Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

Dhirajlal Gandhi College of Technology| India

Dr. J. Vaijayanthimala is a dynamic academic and researcher recognized for her extensive contributions in computer science and engineering, particularly in artificial intelligence, image processing, sensor networks, and intelligent computing systems. Her Google Scholar profile records 16 total citations with an h-index of 2 and i10-index of 0, reflecting her growing scholarly influence across interdisciplinary domains. She has published widely in reputed journals including the ECS Journal of Solid State Science and Technology and Journal of The Electrochemical Society, with research spanning photonic biosensors, AI-based news aggregation, virtual reality accessibility, and smart agriculture. She has co-authored and authored multiple technical books on AI, machine learning, database systems, and data structures, demonstrating her commitment to quality education and knowledge dissemination. Her innovations include patents in automated voice recognition and eco-friendly 3D printing technology. A recipient of the “Innovative Technologist and Dedicated Teaching Professional Award,” she actively contributes as a reviewer for Springer Nature and Elsevier journals. With research interests that merge intelligence, automation, and sustainable technology, Dr. Vaijayanthimala continues to advance computational research and inspire the next generation of scholars.

Profile: Google Scholar

Featured Publications

Vaijayanthimala, J., Pon Bharathi, A., Ramkumar Raja, M., & Arun Kumar, U. (2024). Enhanced sensing of diseased blood samples through one-dimensional MgO-SiO2 photonic crystal sensor. Journal of The Electrochemical Society, 171(10), 107505.

V.M. Manish, J. Vaijayanthimala. (2014). Diminution of packet drop by efficient selection of network route in MANET. International Journal of Computer Science Information Technology (IJCSIT), 5, 1852–1855.

Vaijayanthimala, J., Vaishnavi, K., & Arun Kumar, U. (2025). High-sensitivity terahertz metasensor for cervical cancer diagnosis: Graphene modulation and XGBoost-assisted optimization. Sensors International, 2666–3511, Article 2666.

Vaijayanthimala, J., Alam, M.K., Shqaidef, A., & Mahmoud, O. (2024). Performance evaluation of refractive index biosensor in THz regime for clinical applications: A simulation approach. ECS Journal of Solid State Science and Technology, 13(10), 107005.

Vaijayanthimala, J., & Padma, T. (2019). Synthesis score level fusion based multifarious classifier for multi-biometrics applications. Journal of Medical Imaging and Health Informatics, 9(8), 1673–1680.