Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Published on by Research Awards

Prof. Dr. Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology | India

Dr. K. Ramkumar is a distinguished academician, researcher, and innovator with over twenty-three years of rich teaching and research experience in the field of Engineering and Computer Science. He is presently serving as a Professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. His illustrious academic journey is marked by consistent dedication to research, innovation, and academic excellence. He obtained his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, in 2018, specializing in Security and Privacy in Cloud Computing, a domain of critical importance in the digital era. To further enhance his expertise and broaden his research perspectives, he pursued a Post-Doctoral Fellowship (PDF) at the Federal University of Ceará, Fortaleza, Brazil, in 2023, focusing on Artificial Intelligence and Biomedical Data Analytics. Throughout his career, Dr. Ramkumar has held several prestigious leadership positions in academia, contributing extensively to institutional growth and quality enhancement. He has served as Professor and Head of the Department (CSE) at Rajalakshmi Institute of Technology, Chennai, and earlier as Professor and Associate Dean (Engineering & Technology) at SRM University, Delhi-NCR, Sonepat, Haryana, where he also chaired the Board of Studies. His earlier academic affiliations include SRM Institute of Science and Technology (Vadapalani Campus, Chennai), Kings Engineering College, and Indira Institute of Engineering and Technology, where he also functioned as Director of Placements. His industry exposure includes working with global technology companies such as Satyam Computer Services Ltd. and LogicaCMG Pvt. Ltd. (now CGI), where he held roles as Associate Consultant, IT Consultant, and Project Leader, leading large technical teams across onshore and offshore environments. Dr. Ramkumar’s research interests encompass a broad spectrum of emerging technologies including Cloud Computing Security, Artificial Intelligence, Machine Learning, IoT Frameworks, Blockchain Systems, and Biomedical Data Analytics. His prolific research output includes numerous publications in SCI, Scopus, and Web of Science-indexed journals, with several articles published in reputed platforms such as Elsevier, Springer, Taylor & Francis, and IEEE. His recent works focus on AI-based diabetic risk prediction, intelligent human activity recognition for assistive technologies, quantum image encryption, and deep learning applications for medical imaging. According to his Google Scholar profile, Dr. Ramkumar has achieved over 1,327 citations, with an h-index of 18 and an i10-index of 24, reflecting the global impact and scholarly recognition of his research contributions. His academic influence extends beyond publications, as he has co-supervised several Post-Doctoral Fellows at the Singapore Institute of Technology, demonstrating his commitment to mentoring and nurturing emerging researchers. Dr. Ramkumar has also published and been granted multiple patents across domains such as wireless sensor networks, mobile ad hoc networks, IoT-based monitoring systems, AI-driven diagnostic tools, and environmental pollution control mechanisms, reflecting his strong inclination toward innovation-driven applied research. Dr. K. Ramkumar stands as a dynamic academic leader whose contributions bridge academia, research, and industry, exemplifying excellence in technological innovation, knowledge dissemination, and professional leadership. His remarkable blend of teaching expertise, research achievements, and administrative acumen continues to inspire students, scholars, and peers across the global academic and scientific community.

Profiles: Scopus | Google Scholar

Featured Publications

Ramkumar, K. (2022). A comparative analysis of methods of endmember selection for use in subpixel classification: A convex hull approach. Computational Intelligence and Neuroscience, 2022, Article ID 3770871

Ramkumar, K., Ananthi, N., Brabin, D. R. D., Goswami, P., Baskar, M., & Bhatia, K. K. (2021). Efficient routing mechanism for neighbour selection using fuzzy logic in wireless sensor network. Computers & Electrical Engineering, 94, 107365.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy scalar(s). The European Physical Journal Plus, 139(2), 1–29.

Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy fermion(s). Nuclear Physics B, 1000, 116488.

Ramkumar, K., Medeiros, E. P., Dong, A., de Albuquerque, V. H. C., Hassan, M. R., & Hassan, M. M. (2024). A novel deep learning framework based Swin transformer for dermal cancer cell classification. Engineering Applications of Artificial Intelligence, 133, 108097.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to any mass-dimension for non-degenerate scalars and fermions including light–heavy mixing. The European Physical Journal Plus, 139(2), 169.

 

Xiyuan Huang | Computer Science | Young Innovator Award

Published on by Research Awards

Ms. Xiyuan Huang | Computer Science | Young Innovator Award 

Ms. Xiyuan Huang | Beijing Union University | China 

Ms. Xiyuan Huang, a student researcher at Beijing Union University, has demonstrated exceptional academic brilliance in the field of Artificial Intelligence and time-series analysis. As the first author of a Q1 journal publication in Expert Systems with Applications (IF 7.5), she introduced TCDformer, an innovative transformer-based model for long-term sports momentum prediction, highlighting her ability to design cutting-edge deep learning architectures with real-world impact. Her contributions reflect not only technical expertise but also a forward-looking vision for advancing AI-driven sports analytics and forecasting research.

Author Profile 

Scopus

Education

From the very beginning of her academic journey, Ms. Xiyuan Huang demonstrated a natural curiosity for solving complex problems through technology. Her passion for mathematics, data patterns, and intelligent systems laid the foundation for her engagement with artificial intelligence. She immersed herself in the study of algorithms, statistics, and computational models, finding inspiration in the ability of AI to transform raw data into meaningful predictions. Her early academic focus was not only on acquiring knowledge but also on developing critical thinking skills that would later help her design innovative models. This formative phase nurtured a deep commitment to scientific inquiry, and she quickly emerged as a diligent student with a vision to merge theory with practical applications.

Experience

While still pursuing her academic degree, Ms. Huang stepped into research roles that bridged the gap between academia and applied innovation. She contributed as a student researcher at Beijing Union University, where her responsibilities extended beyond coursework to involve hands-on projects in artificial intelligence. Her professional endeavors have been defined by her ability to take theoretical frameworks and transform them into implementable solutions. By collaborating with mentors and peers, she cultivated a research style rooted in collaboration, technical precision, and forward-looking exploration. She also actively explored opportunities to work on projects that connected AI with real-world forecasting challenges, particularly in the context of sports analytics, reflecting her drive to make research impactful and relevant.

Research Focus

At the heart of Ms. Huang’s scholarly work lies her focus on artificial intelligence, deep learning architectures, and time-series forecasting. Her most distinguished contribution is the development of TCDformer, a novel transformer-based model designed for long-term sports momentum prediction. Published in the prestigious Expert Systems with Applications journal (JCR Q1, IF 7.5), this research highlights her capacity to address complex predictive tasks with elegance and efficiency. The model reflects not only technical innovation but also a fresh perspective on how AI can be leveraged to understand dynamic human behaviors such as sports performance. Beyond her publication, she has been actively engaged in refining methods of time-series analysis, creating pathways for AI-driven insights across domains including healthcare, economics, and social sciences. Her contributions emphasize innovation, methodological rigor, and a drive to explore uncharted territories of AI research.

Accolades and Recognition

Ms. Huang’s research achievements have gained recognition within academic circles for their originality and potential for real-world application. Being the first author of a high-impact international journal publication at an early career stage stands as a testament to her dedication and intellectual maturity. Her work has also drawn appreciation for bridging the divide between theoretical AI research and practical applications, particularly in sports analytics—a growing interdisciplinary field. The Academic Brilliance Recognition Award nomination further reflects the acknowledgment of her scholarly potential and innovative spirit by the wider research community. Each accolade she receives not only honors her current achievements but also sets the stage for her continued advancement in the field of AI.

Impact and Influence

The influence of Ms. Huang’s work extends well beyond her immediate academic environment. By designing TCDformer, she has opened new opportunities for sports scientists, analysts, and trainers to better understand patterns of momentum and performance. This demonstrates the transformative power of AI in reshaping traditional approaches to sports analytics. Her impact also lies in inspiring peers and fellow students to pursue bold research questions, emphasizing that impactful contributions can emerge at any stage of one’s career. Moreover, her focus on time-series forecasting provides a versatile framework that can be adapted to multiple domains, ensuring that her research has a ripple effect across disciplines. Her influence is steadily shaping a culture of curiosity, rigor, and innovation among emerging researchers.

Publications

TCDformer-based momentum transfer model for long-term sports prediction.

Author: Hui Liu, Xiyuan Huang, Jiacheng Gu

Journal: Expert Systems with Applications

Year: 2025

Conclusion

Ms. Xiyuan Huang exemplifies the qualities of a promising researcher whose work combines academic excellence, innovation, and practical relevance. Her early academic pursuits built a strong intellectual foundation, while her professional endeavors and groundbreaking contributions in AI and time-series forecasting demonstrate both skill and vision. Recognized for her achievements through publications and nominations, she continues to inspire peers and expand the impact of AI research in sports analytics and beyond. With her dedication, creativity, and forward-looking mindset, Ms. Huang is poised to make enduring contributions that will shape the future of artificial intelligence and its applications in diverse fields.