Kalaimathi B | Artificial Intelligence | Best Researcher Award

Dr. Kalaimathi B | Artificial Intelligence | Best Researcher Award

Assistant Professor | Sri Ramakrishna Engineering College | India

Dr. Kalaimathi B is an Assistant Professor of Electronics and Communication Engineering with expertise in image processing, artificial intelligence, IoT, and embedded systems. She has authored over 20 research publications in international conferences and journals, achieving 38 citations, an h-index of 4, and an i10-index of 1. Her research focuses on practical innovations in smart transportation, healthcare systems, surveillance, and sustainable technologies. She has demonstrated strong interdisciplinary collaboration through projects involving deep learning, embedded systems, and intelligent automation. Her contributions emphasize real-world impact, including safety, efficiency, and digital transformation, positioning her as a promising researcher in advanced intelligent systems and applied engineering domains.

Citation Metrics

38
30
20
10
0

Citations

38

h-index

4

i10-index

1

Citations

h-index

i10-index

View Google Scholar Profile View ResearchGate Profile View ORCID Profile

Featured Publications


Efficient Power Generation to Automated Street Lights based on Traffic Density

– 5th International Conference on Computing Methodologies, 2021 | Citations: 12


Patient Monitoring and Medicine Dispenser Robot

– International Conference on Computational Intelligence in Engineering, 2022 | Citations: 9


Automatic Headlight Dimmer using Arduino and LDR Sensor

– Turkish Journal of Computer and Mathematics Education, 2021 | Citations: 7


Raspberry PI Based Intelligent Car Parking System

– Smart Technologies, Communication and Robotics (STCR), 2021 | Citations: 5


Current Comparison based Domino with Clamped Bit-Line Current Amplifier for Wide Fan-In Gates

– International Journal of Computer Applications, 2016 | Citations: 2

Lili Zhan | Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr. Lili Zhan | Artificial Intelligence | Best Researcher Award

Associate Professor| Shandong University of Science and Technology | China

Assoc. Prof. Dr. Lili Zhan is a researcher whose work spans remote sensing, Arctic cryosphere monitoring, computer vision, and artificial intelligence–enhanced educational systems. Her scholarship incorporates both physical environmental analysis and advanced data-driven methodologies, with representative contributions including sensitivity analyses of microwave brightness temperature to variations in snow depth on Arctic sea ice, a deep-learning-based remote-sensing scene-classification framework employing EfficientNet-B7, and an improved YOLOv7 instance-segmentation method for ship detection in complex SAR imagery Lili-Zhan. She has also contributed to the design and implementation of intelligent teaching models grounded in contemporary AI and data-centric approaches, demonstrating interdisciplinarity across geospatial sciences and educational technology Lili-Zhan Across these domains, her work reflects a sustained commitment to methodological innovation, integrating state-of-the-art neural architectures with domain-specific challenges in environmental monitoring and maritime situational awareness. Her collaborations often bridge academic research groups focused on cryosphere change, Earth observation, and applied machine learning, enabling the development of tools that support improved climate understanding, maritime safety, and digital-education modernization. Although publication and citation metrics are not specified in the available document, the range of research topics and representative studies indicates a growing scholarly profile with contributions positioned at the intersection of remote-sensing physics and intelligent systems engineering. Collectively, her work holds global societal relevance: enhancing the accuracy of cryospheric measurements supports climate-model improvement and polar-region policy planning; advancing ship-detection techniques contributes to marine governance, environmental protection, and emergency response; and promoting AI-supported pedagogical frameworks aids the digital transformation of education.

Profile: Scopus 

Featured Publications

Zhan, L. (Year). SAR ship target instance segmentation based on SISS-YOLO. Journal Name, Volume(Issue), pages.

Lili Zhan’s work advances the precision of remote-sensing analytics and intelligent detection systems, strengthening global capabilities in environmental monitoring and maritime safety. Her innovations support science-driven decision-making with direct benefits for climate resilience and societal securit

Mona Almutairi | Artificial Intelligence | Best Researcher Award

Ms. Mona Almutairi | Artificial Intelligence | Best Researcher Award

Shaqra University | Saudi Arabia

Ms. Mona Almutairi is a highly motivated computer science graduate with a strong academic foundation and practical experience in system engineering and data management. She completed her Bachelor’s degree in Computer Science from Shaqra University in 2019 with an impressive GPA of 4.19 out of 5, demonstrating consistent academic excellence. Her professional experience includes serving as a System Engineer at the Ministry of Economy and Planning, where she contributed to optimizing systems operations and enhancing digital workflows, as well as volunteering as a Data Entry Assistant at the Ministry of Health, where she efficiently managed and organized large datasets with accuracy and confidentiality. She further enriched her technical expertise through professional courses in Software Engineering from the Saudi Digital Academy and Web Development from the Ministry of Communications and Information Technology, equipping her with up-to-date industry knowledge and coding proficiency. Her research interests lie in software development, data analysis, and emerging technologies that integrate innovation with societal advancement. Ms. Almutairi’s research skills include proficiency in data analysis tools, problem-solving, and the ability to apply algorithmic thinking to real-world challenges. She is also adept at using Microsoft Office and has strong communication, teamwork, and adaptability skills, making her a collaborative and reliable professional. Her dedication to learning and excellence has been recognized through various academic and professional achievements, reflecting her commitment to continuous improvement. Overall, Ms. Almutairi is a forward-thinking computer scientist who combines technical knowledge, analytical capabilities, and professional experience to drive innovation in the field of information technology.

Profiles: Google Scholar | ORCID

Featured Publications

Almutairi, M., & Dardouri, S. (2025). Intelligent hybrid modeling for heart disease prediction. Information, 16(10), 869. Citations: 1