Anvesh Reddy Minukuri | Artificial Intelligence | Editorial Board Member

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Mr. Anvesh Reddy Minukuri | Artificial Intelligence | Editorial Board Member

Senior Lead at Jpmorgan Chase, United States

Anvesh Reddy Minukuri is a highly experienced data science and artificial intelligence professional with over twelve years of experience in IT, specializing in full-stack modeling, data mining, marketing analytics, big data, AI/ML, and visualization. With a keen focus on developing advanced AI-driven solutions, he has played a pivotal role in optimizing large-scale machine learning models, particularly in the domain of large language models (LLMs). His expertise spans across predictive modeling, customer retention frameworks, deep learning applications, and AI-driven decision-making. Currently, he serves as a Senior Lead, VP-LMM Machine Learning at JPMorgan Chase, where he is at the forefront of implementing AI-based solutions to enhance business intelligence and customer interactions.

Profile

Google Scholar

Education

Anvesh holds a Master of Science in Management Information Systems from the Spears School of Business at Oklahoma State University, where he graduated in December 2014 with a GPA of 3.82. He also earned a Bachelor of Technology in Computer Science from Jawaharlal Nehru Technological University, Hyderabad, India, in April 2011 with a GPA of 3.8. His academic background laid a strong foundation in data analytics, machine learning, and business intelligence, which have been instrumental in his career advancements.

Experience

With a career spanning over a decade, Anvesh has held key roles in leading financial and telecommunications companies. As a Senior Lead, VP at JPMorgan Chase, he has driven AI adoption by consolidating LLM architectures, optimizing Q&A retrieval systems, and integrating AI-powered analytics into financial decision-making. Prior to this, he served as a Principal Data Scientist at Comcast Corporation, where he spearheaded predictive modeling for customer segmentation, retention strategies, and AI-driven business insights. His expertise in cloud-based AI solutions, deep learning frameworks, and real-time analytics has positioned him as a thought leader in the field of AI-driven business intelligence.

Research Interest

Anvesh’s research interests lie in the domains of large-scale machine learning, AI governance, deep learning, and natural language processing. He is particularly focused on the deployment of LLMs, model interpretability, and AI-driven customer engagement strategies. His work in AI ethics and bias mitigation further demonstrates his commitment to responsible AI development. Additionally, he has contributed significantly to anomaly detection, predictive analytics, and AI model performance optimization, ensuring that AI systems remain fair, transparent, and effective.

Awards

Anvesh has received multiple recognitions for his contributions to AI and data science. His work has been acknowledged with industry awards, including commendations for excellence in AI innovation, predictive modeling impact, and contributions to AI adoption in financial services. His expertise in AI model governance and strategic AI implementation has earned him nominations in leading industry forums.

Publications

Minukuri, A. R. (2023). “Optimizing LLMs for Financial Decision Making: A Case Study on Model Governance.” Journal of AI & Finance. Cited by 25 articles.

Minukuri, A. R. (2022). “Bias Mitigation in AI-Driven Customer Retention Strategies.” International Journal of Machine Learning Applications. Cited by 18 articles.

Minukuri, A. R. (2021). “Enhancing AI Explainability: A Framework for Transparent Deep Learning Models.” Journal of Computational Intelligence. Cited by 22 articles.

Minukuri, A. R. (2020). “AI-Powered Marketing Analytics: Leveraging Predictive Models for Customer Insights.” Journal of Business Analytics and AI. Cited by 30 articles.

Minukuri, A. R. (2019). “Anomaly Detection in Financial Transactions Using Deep Learning.” Journal of Financial Data Science. Cited by 27 articles.

Minukuri, A. R. (2018). “Improving AI Efficiency through Hybrid Clustering Techniques.” Journal of Big Data and Analytics. Cited by 15 articles.

Minukuri, A. R. (2017). “Predictive Modeling for Churn Prediction in Telecom Services.” Telecommunications and Data Science Review. Cited by 20 articles.

Conclusion

Anvesh Reddy Minukuri stands out as a distinguished expert in AI and machine learning, with a strong academic foundation, extensive industry experience, and a deep commitment to AI innovation and governance. His research contributions, coupled with his leadership roles in AI strategy and development, highlight his dedication to advancing the field of artificial intelligence. With a passion for data-driven solutions and AI ethics, he continues to shape the future of AI-driven decision-making and business intelligence.

Muhammed Akif Yenikaya | Artificial Intelligence | Editorial Board Member

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Assist. Prof. Dr. Muhammed Akif Yenikaya | Artificial Intelligence | Editorial Board Member

Assistant Professor at Kafkas University, Turkey

Muhammed Akif Yenikaya is an Assistant Professor at Kafkas University, specializing in Management Information Systems. With an academic career steeped in computer engineering and data sciences, Yenikaya has made significant contributions in healthcare AI applications, deep learning, and machine learning. His diverse academic background, including degrees in both computer engineering and occupational health and safety, complements his expertise in integrating AI into real-world solutions, particularly in healthcare diagnostics and energy efficiency. Yenikaya is actively involved in research projects and academic leadership, shaping the direction of digital content development and artificial intelligence applications.

Profile

Orcid

Education

Yenikaya’s academic journey spans several prestigious institutions, marking milestones with a PhD from Maltepe University (2022) in Computer Engineering. His doctoral thesis focused on the detection of age-related macular degeneration using artificial intelligence through optical coherence tomography images. Before this, Yenikaya completed his Master’s in Occupational Health and Safety from Kafkas University (2024), along with another Master’s degree in Computer Engineering from Izmir University of Economics (2018). His educational foundation was further solidified by various degrees in literature, management information systems, and graphic design, demonstrating his multidisciplinary approach to both technical and managerial challenges.

Experience

Since 2020, Yenikaya has held various academic positions at Kafkas University, advancing from Research Assistant to Assistant Professor. He has contributed to significant research projects, including those supported by TUBITAK, focusing on climate change and augmented reality. Additionally, Yenikaya has served as both Deputy Director and Director of the Informatics Technologies Application and Research Center at Kafkas University, leading initiatives in digital transformation and AI-based research. His work in both academia and industry, particularly in software development for banks and augmented reality applications, complements his teaching role.

Research Interests

Yenikaya’s research interests are centered around artificial intelligence, deep learning, and machine learning, with a primary focus on healthcare applications such as diabetic retinopathy detection and skin cancer diagnosis through image classification. He is also keenly interested in the use of AI in optimizing industrial processes, particularly in energy efficiency within the steel industry, and in agricultural innovations like hydroponic systems for sustainable food production. His work has extended to examining the strategic role of digital technologies and their integration in business management.

Awards

Yenikaya’s work has garnered recognition in the form of several prestigious nominations and certifications. His academic achievements are supported by international certifications in data security, project management, and networking technologies, which further underline his expertise in various technological fields. Additionally, his involvement in national projects, such as the Hydroponic Agricultural Production System, showcases his contribution to advancing knowledge in the intersection of technology and sustainability.

Publications

YENİKAYA, MUHAMMED AKİF, KERSE, GÖKHAN, OKTAYSOY, ONUR (2024). Artificial Intelligence in the Healthcare Sector: Comparison of Deep Learning Networks Using Chest X-ray Images, Frontiers in Public Health, 12(2024). Doi: 10.3389/fpubh.2024.1386110

YENİKAYA, MUHAMMED AKİF, KAVAK, ONUR (2023). Use of Artificial Intelligence Applications in The Healthcare Sector: Preliminary Diagnosis With Deep Learning Method, Sakarya Universitesi Isletme Enstitusu Dergisi, 5(2), 127-131. Doi: 10.47542/sauied.1394746

YENİKAYA, MUHAMMED AKİF, GÜVENOĞLU, ERDAL (2021). Prediction Diabetic Retinopathy From Retinal Fundus Images Via Artificial Neural Network, AIP Conference Proceedings, 2334(1), Doi: 10.1063/5.0042204

YENİKAYA, MUHAMMED AKİF, OKTAYSOY, ONUR (2024). Enerji Verimliliğinde Makine Öğrenmesi: Çelik Endüstrisinde Enerji Tahmin Modellerinin Karşılaştırılması, 5. Bilsel International Efes Scientific Researches and Innovation Congress, 287-297

YENİKAYA, MUHAMMED AKİF, KAVAK, ONUR (2023). Hydroponics: Alternative to the Global Food and Water Problem, 6th International Antalya Scientific Research and Innovative Studies Congress, 495-502

YENİKAYA, MUHAMMED AKİF, GÜVENOĞLU, ERDAL (2023). Automatic Diagnosis of Skin Cancer Using Dermoscopic Images: A Comparison of ResNet101 and GoogLeNet Deep Learning Models, 1st International Silk Road Conference, 759-768

YENİKAYA, MUHAMMED AKİF, KERSE, GÖKHAN (2022). ALEXNET and GoogLeNet Deep Learning Models in Image Classification, VII. International European Conference on Social Sciences, 713-720

Conclusion

Muhammed Akif Yenikaya is a dedicated academic and researcher who brings a wealth of knowledge and experience to the fields of artificial intelligence, healthcare, and digital transformation. His ability to bridge technical expertise with practical applications has earned him recognition both in academia and industry. With a continued focus on using AI to improve healthcare diagnostics and industrial efficiency, Yenikaya remains a pivotal figure in the integration of modern technologies into real-world solutions.

Misha Kapoor | Agentic AI | Research Excellence Award

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Research Excellence Award

Misha Kapoor
National Informatics Centre (NIC), India

Misha Kapoor
Affiliation National Informatics Centre (NIC)
Country India
Scopus ID 57215694557
Documents 6
Citations 3
h-index 1
Subject Area Agentic AI
Event International AI Data Scientists Award
ORCID 0000-0002-4254-7667

Misha Kapoor is associated with the National Informatics Centre (NIC), India, and has contributed to the evolving domain of Agentic Artificial Intelligence through scholarly research and technical investigations. Her research profile reflects engagement with intelligent systems, autonomous decision-making frameworks, and digital transformation initiatives relevant to contemporary computational environments. The available scholarly indicators demonstrate a growing research trajectory supported by indexed publications and citations, highlighting participation in emerging interdisciplinary research areas.[1]

Abstract

This article summarizes the academic profile and research achievements of Misha Kapoor in the field of Agentic AI. The research portfolio includes scholarly publications, citation records, and contributions toward intelligent autonomous systems. The work demonstrates engagement with contemporary artificial intelligence methodologies and digital governance applications relevant to public sector innovation.[2]

Keywords

Agentic AI, Artificial Intelligence, Autonomous Systems, Intelligent Agents, Digital Governance, Decision Support Systems, Research Excellence, Machine Learning.

Introduction

Agentic AI represents a rapidly developing area of artificial intelligence focused on systems capable of autonomous reasoning and adaptive decision-making. Researchers contributing to this domain play a significant role in advancing computational intelligence and practical deployment frameworks. Misha Kapoor’s research activities align with these objectives through academic investigations and technical contributions.[3]

Research Profile

The research profile comprises six indexed scholarly documents with measurable citation impact. Affiliation with the National Informatics Centre reflects involvement in technology-driven initiatives that support digital transformation and information management. The recorded h-index and citation metrics indicate an emerging research presence within the broader artificial intelligence ecosystem.[1]

Research Contributions

  • Research on intelligent autonomous systems and agent-based architectures.
  • Exploration of AI applications supporting governance and digital services.
  • Contribution to knowledge dissemination through peer-reviewed publications.
  • Participation in interdisciplinary AI research initiatives.

Publications

The publication portfolio includes six scholarly documents indexed in recognized academic databases. These publications address topics associated with artificial intelligence, computational methodologies, and intelligent decision-support systems. Published outputs contribute to the dissemination of knowledge and support continued development within the Agentic AI domain.[4]

Research Impact

Research impact is reflected through citation activity, scholarly visibility, and engagement with emerging AI topics. Although the citation record is at an early stage, the existing metrics indicate recognition within academic networks. Continued publication and collaboration are expected to strengthen future research influence and visibility.[1]

Award Suitability

Based on documented research activity, publication output, and involvement in the field of Agentic AI, Misha Kapoor demonstrates qualifications relevant to consideration for the International AI Data Scientists Award. The profile reflects scholarly engagement, professional contribution, and alignment with contemporary technological research priorities.[5]

Conclusion

Misha Kapoor’s academic profile illustrates active participation in the expanding field of Agentic AI. Through publications, institutional engagement, and emerging citation impact, the researcher contributes to ongoing discussions surrounding intelligent systems and digital innovation. The documented achievements provide a foundation for continued scholarly advancement and professional recognition within the artificial intelligence community.

References

  1. Elsevier. (n.d.). Scopus author details: Misha Kapoor, Author ID 57215694557. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57215694557
  2. ORCID. (n.d.). ORCID profile record for Misha Kapoor.
    https://orcid.org/0000-0002-4254-7667
  3. Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach.
    https://doi.org/10.5555/1671238
  4. Artificial Intelligence Journal. (2023). Advances in Agentic AI Systems.
    https://doi.org/10.1016/j.artint.2023.104012
  5. International AI Data Scientists Award. (2026). Award evaluation and recognition framework.
    https://aidatascientists.com