Kishan Kesari Gupta | Artificial Intelligence | Best Researcher Award

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Mr. Kishan Kesari Gupta | Artificial Intelligence | Best Researcher Award

Software Engineer at Capgemini Technology Services India Limited, India

Mr. Kishan Kesari Gupta is a proficient consultant and researcher with extensive expertise in developing scalable, efficient, and user-focused applications using modern technologies such as React, Vue, Java, Spring Boot, Ruby on Rails, and Python. With significant experience across industries like banking, finance, and insurance, he has successfully delivered complex projects involving microservices, cloud platforms, blockchain, and artificial intelligence. Beyond his professional contributions, he has actively engaged in research, publishing impactful papers with reputed publishers including IEEE, Springer, and Elsevier, while also serving as a reviewer and session chair at international conferences. His thought leadership is further reflected through technical blogs and articles that simplify complex concepts for the wider community. With a strong foundation in continuous learning, team mentorship, and innovation, Mr. Gupta bridges the gap between cutting-edge research and real-world applications, making him a well-rounded professional and a strong candidate for prestigious recognitions in research and technology.

Professional Profile 

Google Scholar

Education

Mr. Kishan Kesari Gupta holds a Master of Science in Computer Applications from Symbiosis International University, Pune, where he honed his technical and analytical abilities with a strong focus on software engineering, programming, and emerging technologies. He also earned his Bachelor of Business Administration in Computer Applications from Savitribai Phule Pune University, where he developed a strong interdisciplinary foundation blending business principles with computer science. His academic journey not only equipped him with comprehensive technical expertise but also instilled a problem-solving mindset, enabling him to bridge theory with practical applications. Through his education, he developed proficiency in programming languages, software design, databases, and system architecture, which later served as the cornerstone of his professional and research endeavors. His continuous pursuit of learning, complemented by engagement in academic research and knowledge sharing, reflects his commitment to both technical excellence and innovation in the field of computer science and information technology.

Experience

Mr. Kishan Kesari Gupta has built a distinguished professional career as a consultant with leading organizations, delivering high-impact projects across finance, insurance, and banking domains. At TechVerito Software Solutions, he worked extensively with modern frameworks such as Vue.js, React, Ruby on Rails, Java, and Spring Boot, developing scalable applications and deploying microservices through Docker and CI/CD pipelines. His expertise extended to building RESTful APIs, implementing secure architectures, and contributing to test-driven development practices. Later, at Capgemini, he contributed to strategic digital transformation initiatives, including customer onboarding and digital asset solutions for global banks, leveraging technologies such as blockchain, cloud computing, and artificial intelligence. His work consistently emphasized innovation, system efficiency, and user-centric design, while he actively contributed to agile processes through sprints, PR reviews, and deployment strategies. With experience in leadership, technical mentoring, and project management, he has demonstrated the ability to translate complex requirements into impactful technology-driven outcomes.

Research Focus

Mr. Kishan Kesari Gupta’s research focus lies at the intersection of artificial intelligence, machine learning, computer vision, blockchain, and scalable software systems. He has contributed significantly to academic research, with publications in reputed platforms such as IEEE, Springer, and Elsevier, covering topics like machine vision for heart health monitoring and human activity recognition using deep learning and CNN architectures. His work emphasizes applying advanced computational methods to solve real-world challenges, particularly in healthcare analytics, automation, and secure digital ecosystems. Additionally, he explores generative AI, large language models, and agentic AI, examining their potential for reshaping industries and human-technology interaction. His interest extends to leveraging blockchain for secure financial transactions and digital asset management, merging his industry experience with academic inquiry. By blending theoretical advancements with practical applications, he contributes to both the academic community and the technology industry, striving to build impactful solutions that are innovative, ethical, and future-ready.

Award and Honor

Mr. Kishan Kesari Gupta has been recognized for his dual contributions to both industry and academia, positioning him as a strong candidate for awards in research and technology innovation. His role as a session chair and research reviewer at international conferences reflects the academic community’s trust in his expertise and leadership. His impactful research publications with globally recognized publishers highlight his commitment to advancing knowledge and delivering practical solutions. Additionally, his leadership in major industry projects, particularly in digital transformation and financial technology, has earned him credibility as a technology innovator. His blogs and articles further enhance his reputation, as they simplify complex concepts and provide valuable insights to professionals and learners worldwide. These achievements, combined with his ongoing exploration of artificial intelligence, machine learning, and blockchain, underline his stature as a thought leader deserving of recognition through awards that honor excellence in research and applied technology.

Publication Top Notes

Title: Framework-Agnostic JavaScript Component Libraries: Benefits, Implementation Strategies, and Commercialization Models
Authors: KK Gupta, P Awasthi, M Shaik, PR Kaveri
Year: 2024
Citations: 6

Title: Understanding the need for machine learning as a solution for financial analysis of IT industries
Authors: KK Gupta, A Anil, A Anand, PR Kaveri
Year: 2020
Citations: 1

Title: Development of an Autonomous Weeding Robot for Roadside Weeds
Authors: Y Matsushita, KK Gupta, Y Fujii, DT Tran, JH Lee
Year: 2025

Title: iSpace Coding: A System for User-Defined Flexible Spatial Functions in Intelligent Spaces
Authors: S Yoshida, KK Gupta, Y Fujii, DT Tran, JH Lee
Year: 2025

Title: Integrating Human Motion Dynamics in CNN Architecture to Recognize Human Activity from Different Camera Angles
Authors: KK Gupta, JH Lee, PR Kaveri, P Awasthi
Year: 2025

Title: Implementing Machine Vision Process to Analyze Echocardiography for Heart Health Monitoring
Authors: KK Gupta, A Anil, PR Kaveri
Year: 2022

Conclusion

The publication record of Mr. Kishan Kesari Gupta reflects a strong and evolving research trajectory that bridges computer science, artificial intelligence, and applied technologies. His contributions span diverse areas such as machine learning for financial analysis, computer vision for healthcare, deep learning for human activity recognition, and innovative applications in robotics and intelligent spaces. The cited works, particularly in IEEE and Springer, indicate both academic relevance and growing recognition within the research community. His most cited paper on framework-agnostic JavaScript component libraries highlights his ability to merge practical software engineering with academic exploration. Recent works in robotics, human motion dynamics, and medical imaging demonstrate his focus on impactful, interdisciplinary research with real-world applications. Collectively, his publications showcase technical depth, innovation, and a commitment to advancing knowledge, positioning him as a promising researcher whose work continues to contribute meaningfully to both academia and industry.

Ritu Tanwar | Artificial intelligence | Best Researcher Award

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Ms. Ritu Tanwar | Artificial intelligence | Best Researcher Award

Research Scholar, NIT Uttarakhand, India

Ms. Ritu Tanwar is a dedicated Research Scholar at the National Institute of Technology, Uttarakhand, India, specializing in stress and emotion recognition through advanced machine learning techniques. Her innovative research harnesses deep learning and artificial intelligence to interpret physiological signals, contributing significantly to the field of affective computing. Ritu’s academic journey and teaching roles underline her commitment to advancing both theoretical and practical aspects of her research.

Profile

Scopus

Research for “Best Researcher Award” for Ms. Ritu Tanwar

Strengths for the Award

Ms. Ritu Tanwar, currently pursuing her PhD at the National Institute of Technology, Uttarakhand, has demonstrated exceptional strengths in her field of research. Her primary area of focus—stress and emotion recognition through physiological signals—highlights her deep engagement with cutting-edge technology and data analysis. Ritu’s work utilizes advanced techniques in deep learning and machine learning to address significant challenges in affective state recognition.

Innovative Research Contributions: Ritu’s research integrates multimodal physiological signals to enhance stress recognition, showcasing her ability to develop and implement novel frameworks. Her attention-based hybrid deep learning models for wearable stress recognition, published in prestigious journals like Engineering Applications of Artificial Intelligence and Computers and Electrical Engineering, underline her proficiency in blending theory with practical application.

High-Impact Publications: Her publications in high-impact journals and conferences, including Computers in Biology and Medicine and the International Conference on Artificial Intelligence, reflect the substantial impact of her work on the field. Her innovative models, such as the CNN-LSTM based stress recognition system, are well-received and contribute to advancing the state of the art in affective computing.

Diverse Expertise: Ritu’s skill set spans various domains, from deep learning and artificial intelligence to data analysis and signal processing. Her ability to apply these skills effectively in her research demonstrates a well-rounded expertise that is crucial for a leading researcher.

Areas for Improvement

While Ms. Tanwar’s achievements are commendable, there are areas where she could further enhance her profile:

Broader Research Collaboration: Expanding her collaborative network with researchers from diverse fields could provide new insights and foster interdisciplinary approaches. Engaging in more collaborative projects could also increase the visibility and applicability of her research outcomes.

Broadened Publication Scope: Although Ritu has published extensively, diversifying her publication portfolio to include more interdisciplinary journals or higher-impact venues could further amplify the reach and influence of her research.

Enhanced Outreach: Increasing her participation in academic and industry conferences, workshops, and seminars could boost her professional network and provide more platforms to showcase her research. Additionally, contributing to review articles or special issues in her field could enhance her visibility as a thought leader.

Education 🎓

Ms. Tanwar is currently pursuing a PhD in Electronics Engineering at the National Institute of Technology, Uttarakhand, India, focusing on developing a deep learning framework for affective state recognition using multimodal physiological signals (April 2021-present). She earned her M.Tech. in Electronics & Communication Engineering from the University Institute of Engineering & Technology, Kurukshetra, India, with a thesis on emotion recognition from audio signals (July 2018). Her foundational B.Tech. in Electronics & Communication Engineering was also completed at the same institute (July 2013).

Experience 💼

Ms. Tanwar has a robust academic background, having worked as a Teaching Assistant at the National Institute of Technology, Uttarakhand, where she taught courses on Microcontroller and Interfacing, Digital Signal Processing, and Speech & Image Processing. Her research experience includes contributions as an Assistant/Associate Supervisor for undergraduate students and active participation in administrative and outreach activities, including her roles as Session Coordinator and Reviewer for the IC2E3 IEEE Conference.

Research Interests 🔬

Ms. Tanwar’s research interests are centered around stress and emotion recognition, physiological signals, and advanced data analysis techniques. She specializes in applying deep learning, machine learning, and artificial intelligence to improve the accuracy and applicability of affective state recognition systems.

Awards 🏆

Senior Research Fellow Scholarship (2021-present): Awarded for her exceptional research capabilities and contributions to her field.

Publication Recognition: Her work has been accepted and recognized in leading journals and conferences, reflecting her significant contributions to the field of artificial intelligence and machine learning.

Publications Top Notes

Tanwar, R., Phukan, O. C., Singh, G., Pal, P. K., & Tiwari, S. (2024). Attention based hybrid deep learning model for wearable based stress recognition. Engineering Applications of Artificial Intelligence, 127, 107391.

Tanwar, R., Singh, G., & Pal, P. K. (2024). A Hybrid Transposed Attention Based Deep Learning Model for Wearable and Explainable Stress Recognition. Computers and Electrical Engineering (Accepted).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Explainable Artificial Intelligence System For Stress Recognition Using Multimodal Physiological Signals. Computers in Biology and Medicine (under review).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Stress-Wed: Stress recognition autoencoder using Wearables Data. In Second International Conference on Artificial Intelligence: Towards Sustainable Intelligence. Springer (Accepted).

Conclusion

Ms. Ritu Tanwar’s research on stress and emotion recognition using physiological signals is both innovative and impactful, making her a strong candidate for the “Best Researcher Award.” Her contributions to deep learning and machine learning in affective computing are significant, and her academic and teaching experiences add to her profile as a dedicated and knowledgeable researcher. By addressing areas for improvement, such as expanding collaboration and publication scope, Ritu can further strengthen her position as a leading researcher in her field. Her ongoing research promises to make substantial contributions to both theoretical and applied aspects of artificial intelligence and emotion recognition.