Ikram ul Haq | Artificial Intelligence | Best Researcher Award

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Best Researcher Award

Ikram ul Haq
BIT

Ikram ul Haq
Affiliation BIT
Country Pakistan
Documents 1479
Citations 30,887
h-index 77
Subject Area Artificial Intelligence
Event International AI Data Scientists Award

Ikram ul Haq is a distinguished researcher associated with BIT, Pakistan, whose scholarly contributions have significantly influenced the advancement of Artificial Intelligence and related computational disciplines. His extensive publication portfolio, high citation impact, and sustained academic productivity demonstrate a strong commitment to scientific inquiry and innovation. The breadth of his research output reflects continuous engagement with emerging technologies, interdisciplinary collaboration, and the practical application of intelligent systems across diverse domains.[1]

Abstract

This article presents an overview of the academic achievements and research influence of Ikram ul Haq. Through a substantial body of scholarly work, he has contributed to Artificial Intelligence research, producing publications that have received significant attention from the global scientific community. His research impact is reflected through extensive citations and a strong h-index, indicating sustained relevance and influence within the field.[1]

Keywords

Artificial Intelligence, Machine Learning, Computational Intelligence, Data Analytics, Research Excellence, Knowledge Discovery, Intelligent Systems.

Introduction

Artificial Intelligence has become one of the most influential scientific disciplines of the modern era, enabling advances in automation, predictive analytics, intelligent decision-making, and data-driven innovation. Researchers who contribute extensively to this field help shape future technologies and provide solutions to complex societal and industrial challenges. Ikram ul Haq has established a notable academic presence through sustained scholarly activity and impactful research contributions that support the continued evolution of intelligent systems.[2]

Research Profile

  • Affiliation: BIT, Pakistan.
  • Primary research domain: Artificial Intelligence.
  • Total scholarly documents: 1,479.
  • Total citations: 30,887.
  • h-index: 77.

Research Contributions

Ikram ul Haq’s research contributions span a broad range of Artificial Intelligence topics, including intelligent computing, machine learning methodologies, data analytics, and computational modeling. His work has contributed to the advancement of scientific understanding while supporting practical applications across academic and industrial environments. Through collaborative research efforts and consistent publication activity, he has participated in the global exchange of knowledge and technological innovation.[2]

Publications

With 1,479 scholarly publications, Ikram ul Haq demonstrates exceptional research productivity. His publication record reflects long-term engagement with emerging scientific challenges and highlights a commitment to advancing Artificial Intelligence through rigorous investigation and dissemination of findings. The diversity of topics covered within his research portfolio illustrates both depth and breadth of expertise.[1]

Research Impact

The impact of scholarly research is often measured through citation performance and recognition by the academic community. Accumulating more than 30,887 citations and maintaining an h-index of 77, Ikram ul Haq has achieved significant visibility within the research landscape. These indicators suggest that his work continues to influence subsequent studies and contributes meaningfully to ongoing developments in Artificial Intelligence and related fields.[1]

Award Suitability

The Best Researcher Award recognizes individuals who demonstrate sustained scholarly excellence, measurable scientific impact, and meaningful contributions to research advancement. Based on his publication volume, citation metrics, and influence within the Artificial Intelligence community, Ikram ul Haq represents a strong candidate for recognition. His achievements align closely with the objectives of the International AI Data Scientists Award, which promotes innovation, scientific excellence, and global research leadership.[3]

Conclusion

Ikram ul Haq’s academic career reflects a substantial contribution to Artificial Intelligence research through a combination of productivity, influence, and scholarly engagement. His extensive publication portfolio, strong citation record, and continuing impact on scientific literature illustrate a sustained commitment to advancing knowledge. These accomplishments support his consideration for the Best Researcher Award and highlight his role within the broader research community.[1]

References

  1. Google Scholar. (n.d.). Scholar profile and citation metrics of Ikram ul Haq.
    https://scholar.google.com/citations?user=tIrmMlYAAAAJ&hl=en&oi=sra
  2. XAAI-ledger: An explainable CNN-transformer-based multi-modal deep learning framework for early detection of melanoma and non-melanoma skin cancers using dermoscopic and clinical data.
    https://doi.org/10.1016/j.bspc.2026.110410
  3. International AI Data Scientists Award. (n.d.). Award evaluation and recognition framework.
    https://aidatascientists.com/

Preety Shoran | Christ University | Best Researcher Award

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Best Researcher Award

Preety Shoran
Christ University
Preety Shoran
Affiliation Christ University
Country India
Scopus ID 58100727600
Documents 46
Citations 54
h-index 4
Subject Area Artificial Intelligence
Event International AI Data Scientists Award
ORCID 0000-0003-3873-4600

Preety Shoran of Christ University, India. Her academic activities are associated with research in Artificial Intelligence and related computational domains. Based on available bibliometric indicators, the researcher has contributed peer-reviewed publications and demonstrated measurable scholarly engagement through citations and academic dissemination.[1]

Abstract

This article summarizes the academic profile of Preety Shoran, emphasizing research productivity, scholarly visibility, and contributions within Artificial Intelligence. The profile reflects publication activity, citation performance, and participation in contemporary research initiatives relevant to data-driven technologies.[1]

Keywords

Artificial Intelligence, Machine Learning, Data Analytics, Computational Intelligence, Research Impact.

Introduction

Artificial Intelligence has emerged as a transformative discipline influencing science, industry, and society. Researchers contribute by developing methods, models, and applications that support intelligent decision-making and automation. Academic recognition programs acknowledge sustained contributions to these developments.[2]

Research Profile

Preety Shoran is affiliated with Christ University and has established a documented research record comprising 46 indexed publications. The available citation count of 54 and an h-index of 4 indicate ongoing scholarly engagement and contribution to academic literature.[1]

Research Contributions

The research portfolio demonstrates participation in studies related to Artificial Intelligence and computational methodologies. Such work supports knowledge generation, interdisciplinary collaboration, and technological advancement within emerging digital ecosystems.[3]

Publications

  • Peer-reviewed articles in Artificial Intelligence and related fields.
  • Conference proceedings and scholarly communications.
  • Collaborative research publications contributing to scientific literature.

Research Impact

Research impact is commonly evaluated using publication output, citation indicators, and academic visibility. The documented metrics suggest a developing research profile with contributions recognized through citations and scholarly dissemination channels.[1]

Award Suitability

Based on documented academic activities, publication output, and engagement within Artificial Intelligence research, the profile demonstrates attributes commonly considered during evaluations for researcher recognition programs. Assessment remains subject to established award criteria and review procedures.[4]

Conclusion

Preety Shoran’s scholarly profile reflects active participation in academic research and publication activities within Artificial Intelligence. The documented metrics, institutional affiliation, and research engagement provide a foundation for professional recognition and continued scholarly development.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Preety Shoran, Author ID 58100727600. Scopus.
    https://www.scopus.com/pages/authors/58100727600
  2. Orcid author details: Preety Shoran.
    https://orcid.org/0000-0003-3873-4600
  3. Artificial Intelligence Research Overview.
    https://doi.org/10.1016/j.artint.2023.104001
  4. International AI Data Scientists Award Evaluation Framework.
    https://aidatascientists.com/

Ioannis Karamitsos | Generative AI | Innovative Research Award

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Innovative Research Award

Ioannis Karamitsos
Rochester Institute of Technology

Ioannis Karamitsos
Affiliation Rochester Institute of Technology
Country United Arab Emirates
Scopus ID 6506423886
Documents 57
Citations 618
h-index 12
Subject Area Generative AI
Event International AI Data Scientists Award
ORCID 0000-0001-6106-6423

Ioannis Karamitsos is a researcher affiliated with Rochester Institute of Technology whose academic activities focus on Generative Artificial Intelligence, intelligent systems, and advanced computational technologies. His scholarly work contributes to the growing body of knowledge surrounding machine learning applications, AI-enabled innovation, and data-driven decision-making. With a documented record of publications, citations, and interdisciplinary collaboration, his research profile reflects continued engagement in addressing contemporary challenges in artificial intelligence and digital transformation. The following article presents a structured overview of his academic background, research contributions, publication record, and suitability for recognition through the Innovative Research Award.[1]

Abstract

This article summarizes the academic profile and research achievements of Ioannis Karamitsos. His work within Generative AI contributes to the development of intelligent computational frameworks, machine learning methodologies, and practical AI applications. Through sustained publication activity and scholarly engagement, his research demonstrates measurable academic impact and relevance within contemporary artificial intelligence research.[1]

Keywords

Generative AI, Artificial Intelligence, Machine Learning, Computational Intelligence, Data Science, Innovation, Digital Transformation.

Introduction

Artificial intelligence has become a significant driver of innovation across academia and industry. Within this rapidly evolving environment, researchers play a critical role in advancing theoretical understanding and practical implementation of intelligent systems. Ioannis Karamitsos contributes to this landscape through research focused on Generative AI and related computational technologies. His work aligns with ongoing efforts to improve automation, intelligent decision-making, and knowledge generation across diverse domains.[2]

Research Profile

According to available scholarly metrics, Ioannis Karamitsos has authored 57 indexed documents and accumulated 618 citations, resulting in an h-index of 12. These indicators suggest consistent research productivity and influence within the academic community. His work spans areas associated with Generative AI, intelligent computing systems, and digital innovation, reflecting a multidisciplinary approach to research and development.[1]

Research Contributions

  • Research and development in Generative Artificial Intelligence methodologies.
  • Application of machine learning techniques for intelligent decision support.
  • Contribution to interdisciplinary digital transformation initiatives.
  • Collaboration across academic and technological research environments.

Publications

The publication portfolio of Ioannis Karamitsos includes peer-reviewed journal articles, conference proceedings, and collaborative research outputs. These publications address important themes related to artificial intelligence, intelligent systems, and emerging computational technologies. The body of work contributes to ongoing scholarly discussions regarding innovation, automation, and responsible AI implementation.[3]

Research Impact

Citation metrics provide evidence of engagement by the broader research community. With 618 citations, the published work has been referenced by scholars across related fields, demonstrating relevance and visibility within contemporary AI research. Such impact indicators support the significance of the researcher’s contributions and their role in advancing knowledge within Generative AI and computational intelligence.[1]

Award Suitability

The academic profile presented here demonstrates qualities commonly associated with recipients of research excellence awards. Research productivity, citation performance, scholarly visibility, and contributions to emerging technologies collectively indicate a strong foundation for recognition. His work in Generative AI reflects sustained engagement with scientific advancement and innovation-oriented research activities.[1]

Conclusion

Ioannis Karamitsos has established a notable scholarly presence through his research contributions, publication record, and measurable academic impact. His activities within Generative AI contribute to the advancement of intelligent technologies and support ongoing innovation in artificial intelligence. The combination of research productivity, citation influence, and interdisciplinary engagement highlights his relevance within the contemporary scientific community.

References

  1. Elsevier. (n.d.). Scopus author details: Ioannis Karamitsos, Author ID 6506423886. Scopus.
    https://www.scopus.com/pages/authors/6506423886
  2. ORCID. (n.d.). Researcher profile and scholarly activities.
    https://orcid.org/0000-0001-6106-6423
  3. Artificial Intelligence Journal. (2023). Advances in Generative AI and Intelligent Systems.
    DOI: https://doi.org/10.1016/j.artint.2023.104012

Yang Zhao | Artificial Intelligence | Best Researcher Award

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Best Researcher Award

Yang Zhao
Affiliation College of Oceanic and Atmospheric Sciences, Ocean University of China
Country China
Google Scholar View Profile 
Documents 75
Citations 2139
h-index 27
Subject Area Artificial Intelligence
Event International AI Data Scientists Award
ORCID 0000-0002-3306-9835

Yang Zhao

College of Oceanic and Atmospheric Sciences, Ocean University of China

Yang Zhao is a researcher at the College of Oceanic and Atmospheric Sciences, Ocean University of China. His academic work reflects the growing integration of artificial intelligence, environmental analytics, and data-driven scientific methodologies. With 75 indexed publications, 2,139 citations, and an h-index of 27, Zhao has developed a notable scholarly profile supported by consistent research productivity and international visibility.[1]

Abstract

This article summarizes the research achievements, academic impact, and professional contributions of Yang Zhao. His work demonstrates the application of advanced analytical and artificial intelligence techniques to environmental and oceanic science, contributing to interdisciplinary scientific progress.[2]

Keywords

Artificial Intelligence, Ocean Science, Environmental Analytics, Machine Learning, Data Science, Research Impact.

Introduction

The increasing importance of data-intensive research has accelerated the adoption of artificial intelligence across scientific disciplines. Yang Zhao’s work reflects this trend by combining computational approaches with environmental and oceanographic applications.[1]

Research Profile

Zhao has authored 75 scholarly documents and accumulated 2,139 citations. His h-index of 27 demonstrates sustained influence within the academic community and highlights the relevance of his contributions to ongoing scientific research.[1]

Research Contributions

His research emphasizes predictive modeling, environmental data interpretation, and the integration of artificial intelligence technologies into scientific workflows. These contributions support improved understanding of complex environmental systems and decision-making processes.[3]

Publications

  • Peer-reviewed journal articles.
  • Interdisciplinary environmental studies.
  • Artificial intelligence and modeling research.

Research Impact

The citation performance of Zhao’s publications demonstrates continued scholarly engagement and recognition. His work contributes to the broader advancement of computational methods in environmental science and related disciplines.[1]

Award Suitability

Based on publication productivity, citation impact, and interdisciplinary scientific contributions, Yang Zhao demonstrates qualities consistent with academic recognition programs such as the International AI Data Scientists Award.[4]

Conclusion

Yang Zhao’s research profile illustrates a sustained commitment to scientific excellence. His contributions to artificial intelligence applications, environmental research, and interdisciplinary collaboration support his recognition as a distinguished researcher.

References

  1. Google Scholar Author Profile: Yang Zhao.
    https://scholar.google.com.hk/citations?user=CO4iwFkAAAAJ&hl=zh-CN
  2. ORCID. Research Profile of Yang Zhao.
    https://orcid.org/0000-0002-3306-9835
  3. Environmental Modelling & Software. DOI Reference.
    https://doi.org/10.1016/j.envsoft.2020.104776
  4. International AI Data Scientists Award.
    https://aidatascientists.com/

Zhi Liu | Artificial Intelligence | Research Excellence Award

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Prof. Zhi Liu | Artificial Intelligence | Research Excellence Award

Professor | Shandong University | China

Prof. Zhi Liu is a prominent researcher in Artificial Intelligence, specializing in machine learning, deep neural networks, and intelligent data analysis. His work focuses strongly on medical imaging, biomedical signal processing, and computer vision applications. He integrates domain knowledge with advanced AI models to enhance accuracy, robustness, and interpretability. His contributions include weakly supervised learning, multi-scale feature fusion, transformer-based models, and time-series analysis. Through interdisciplinary research, he advances impactful AI solutions for healthcare and intelligent systems.

Prof Zhi Liu
Shandong University
Artificial Intelligence | China

Citation Metrics (Scopus)

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0

Citations
4,806

Documents
250

h-index
33


View Scopus Profile

Featured Publications

Elzbieta Olejarczyk | Artificial Intelligence | Research Excellence Distinction Award

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Assoc. Prof. Dr. Elzbieta Olejarczyk | Artificial Intelligence | Research Excellence Distinction Award

Senior Reasearcher at Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences | Poland

Assoc. Prof. Dr. Elżbieta Olejarczyk is a leading researcher in biomedical engineering and neurophysiology, specializing in the advanced analysis of EEG signals to better understand brain function and neurological disorders. Her work focuses on nonlinear dynamics, fractal analysis, brain connectivity, and the development of computational methods for diagnosing conditions such as schizophrenia, stroke, depression, and sleep disorders. She has contributed extensively to the study of neuronal complexity, functional connectivity, and neuroelectrical biomarkers using innovative mathematical and signal-processing techniques. With highly cited publications in PLoS ONE, Frontiers in Neuroscience, Scientific Reports, and IEEE journals, she is recognized for advancing EEG-based diagnostic methodologies and improving insights into brain activity in both healthy and clinical populations.

 

Citation Metrics (Google Scholar)

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1,487

i10-index 29

h-index
19

                             Citations
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View Google Scholar Profile

Featured Publications

Peik Foong Yeap | Artificial Intelligence | Best Academic Researcher Award

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Dr. Peik Foong Yeap | Artificial Intelligence | Best Academic Researcher Award

Senior Lecturer at University of Newcastle | Singapore

Dr. Yeap Peik Foong is a distinguished academic and researcher whose career reflects a deep commitment to advancing knowledge in strategic management, organisational development, cross-cultural management, sustainability practices, and innovation within higher education and industry. Renowned for her interdisciplinary perspective, she has contributed extensively to scholarly literature through impactful journal articles, book chapters, and international conference presentations that explore themes such as digital transformation, human–AI collaboration, leadership effectiveness, consumer behaviour, knowledge management, environmental sustainability, and community-based tourism. Her work is recognized for its ability to merge theoretical frameworks with real-world applications, offering insights that guide policy development, organisational strategy, and educational leadership. She has played influential roles in shaping academic programs, strengthening research culture, and supporting curriculum innovation, while also contributing actively as a reviewer, editorial board member, and examiner for reputable journals, conferences, and institutions worldwide. Her research leadership is further demonstrated through her involvement in numerous funded projects that address emerging challenges in digital well-being, workplace resilience, global responsibility, cybersecurity, internationalisation of higher education, and interorganisational collaboration. Known for her mentorship and supervision of postgraduate candidates, she has supported research that spans management, marketing, organisational behaviour, and industry-specific strategic studies, helping shape future scholars and professionals. Her consistent engagement with global academic communities, coupled with her ability to foster collaborative networks, reflects her dedication to elevating research standards and promoting sustainable, innovative, and culturally aware practices across sectors. Dr. Yeap’s body of work positions her as a respected thought leader whose scholarly contributions and service continue to influence contemporary debates and future directions in management, education, and organisational sustainability.

Profile: Scopus

Featured Publications

Ha, H., Yeap, P. F., Loh, H. S., & Pidani, R. (2025). Environmental sustainability and CSR practices by banks in Indonesia, Malaysia, and Singapore.

Tan, K. L., Yeap, P. F., Cheong, K. C. K., & Shanu, R. (2025). Crafting an organizational strategy for the new era: A qualitative study of artificial intelligence transformation in a homegrown Singaporean hotel chain.

Tan, K.-L., Loganathan, S. R., Pidani, R. R., Yeap, P.-F., Ng, D. W. L., Chong, N. T. S., Liow, M. L. S., Cheong, K. C.-K., & Yeo, M. M. L. (2024). Embracing imperfections: A predictive analysis of factors alleviating adult leaders’ digital learning stress on Singapore’s lifelong learning journey.

Yeap, P. F., & Liow, M. L. S. (2023). Tourist walkability and sustainable community-based tourism: Conceptual framework and strategic model.

Ong, H. B., Chong, L. L., Choon, S. W., Tan, S. H., Yeap, P. F., & Kasuma, N. M. H. (2022). Retaining skilled workers through motivation: The Malaysian case.

Lee, Y. W., Dorasamy, M., Ahmad, A. A., Jambulingam, M., Yeap, P. F., & Harun, S. (2021). Synchronous online learning during movement control order in higher education institutions: A systematic review.

Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

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Dr. Bhavesh Kataria | AI and Machine Learning | AI & Machine Learning Award

Post-Doctoral Fellow at Emory University | United States

Dr. Bhavesh Kataria is a highly accomplished academician, researcher, and innovator in Computer Engineering, recognized globally for his leadership in Artificial Intelligence, Machine Learning, and Digital Image Processing. His professional journey spans academia and research institutions across India and the United States, including his role at Emory University, where he contributes to advanced AI-driven healthcare analytics and digital pathology solutions. With a Ph.D. focused on Optical Character Recognition of Sanskrit Manuscripts using Convolutional Neural Networks, Dr. Kataria has combined technical precision with deep domain expertise to address challenges in multilingual text recognition and medical imaging. His scholarly portfolio includes numerous publications in reputed international journals, multiple granted patents, and several authored books covering cutting-edge topics in AI, cloud computing, and web technologies. An active member of prestigious organizations such as IEEE and ACM, he serves on editorial boards of international journals and as a reviewer for globally recognized publishers like Springer Nature and Science Publishing Group. He has also chaired sessions and reviewed Ph.D. theses, contributing significantly to the academic ecosystem. Dr. Kataria’s pioneering innovations, such as AI-based network visualization tools, smart teaching devices, and healthcare monitoring systems, underscore his commitment to translational research and practical AI applications. Honored with awards including the Best Researcher Award and Teaching Excellence Award, he exemplifies a blend of scholarly excellence, innovation, and mentorship. His dedication to advancing intelligent systems and promoting interdisciplinary research continues to inspire global collaboration in emerging computational technologies.

Profiles: Scopus | ORCID

Featured Publications

Kataria, B., & Jethva, H. B. (2024, September 30). Decentralized security mechanisms for AI-driven wireless networks: Integrating blockchain and federated learning.

Kataria, B. (2024, June 2). Automated detection of tuberculosis using deep learning algorithms on chest X-rays.

Shivadekar, S., Kataria, B., Hundekari, S., Wanjale, K., Balpande, V. P., & Suryawanshi, R. (2023). Deep learning based image classification of lungs radiography for detecting COVID-19 using a deep CNN and ResNet 50.

Shivadekar, S., Kataria, B., Limkar, S., Wagh, K., Lavate, S., & Mulla, R. (2023, June 15). Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process.

Kataria, B., Jethva, H. B., Shinde, P. V., Banait, S. S., Shaikh, F., & Ajani, S. (2023, April 30). SLDEB: Design of a secure and lightweight dynamic encryption bio-inspired model for IoT networks.

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

Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

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Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

Assistant Professor, Prof. Ramkrishna More Arts, Commerce & Science College, India

Dr. Santosh Jagtap, Assistant Professor at Prof. Ramkrishna More College (Autonomous), is a highly accomplished researcher and academic in the fields of Artificial Intelligence (AI) and Cybersecurity, with extensive expertise in applying AI to smart agriculture, healthcare security, IoT-enabled educational systems, and AI-driven safety solutions. Dr. Jagtap holds advanced academic qualifications and has developed a distinguished research profile that emphasizes practical applications of emerging technologies to address societal challenges. His work integrates machine learning, blockchain, IoT, and real-time data processing, producing innovative solutions in areas such as intelligent irrigation systems, plant disease detection, AI-based emotion recognition for safety alerts, and secure healthcare frameworks. Over his career, Dr. Jagtap has contributed significantly to international research projects and collaborative studies, producing high-impact publications in reputed journals and conference proceedings, such as Materials Today: Proceedings, international conferences on electronics, computing, and applied AI. He has also been recognized for innovation through patent awards, notably for AI-based plant disease identification systems, reflecting his focus on technology transfer and real-world impact. Dr. Jagtap has played an active role in mentoring students, guiding research projects, and participating in professional networks that foster academic and technological growth. He has demonstrated a consistent record of research excellence, with a total of 78 citations across 4 Scopus-indexed publications and an h-index of 3, reflecting the growing impact of his work.

Profile: GOOGLE SCHOLAR | SCOPUS

Featured Publications

  • Jagtap, S. T., Phasinam, K., Kassanu. (2022). Towards application of various machine learning techniques in agriculture. Materials Today: Proceedings, 51, 793–797. 70 citations.

  • Jagtap, S. T., Thakar, (2021). A framework for secure healthcare system using blockchain and smart contracts. Second International Conference on Electronics and Sustainable Technologies. 22 citations.

  • Jagtap, S. T., Jagdale, K. C., & Thakar, C. M. (2023). Identification of plant disease device using artificial intelligence. IN Patent 391523-001. –

  • Pratiksha Bhise, D. S. J., & Jagtap, S. T. (2024). AI-driven emergency response system for women’s safety using real-time location and heart rate monitoring. IJRPR. –

  • Keskar,  A., Jagtap, S. T., et al. (2021). Big data preprocessing frameworks: Tools and techniques. Design Engineering, 1738–1746.