Dr. Roseline Ogundokun | Intrusion Detection System | Best Researcher Award

Dr. Roseline Ogundokun | Intrusion Detection System | Best Researcher Award

Dr. Roseline Ogundokun, Landmark University Omu-Aran, Nigeria

Roseline Oluwaseun Ogundokun is a distinguished academic and researcher in computer science, born in Zaria, Nigeria. Currently serving as a lecturer and researcher at Landmark University, she specializes in machine learning, artificial intelligence, and computer vision. With a strong commitment to education and innovative research, Roseline has made significant contributions to advancing sustainable development goals through technology. She is also involved in mentoring students in STEM fields and has a passion for fostering future generations of scientists.

Professional Profile

Google Scholar

Researcher Suitability Summary for the Best Researcher Award: Roseline Oluwaseun Ogundokun

Based on her extensive research output, significant contributions to academia, and commitment to mentoring and inclusive practices, Dr. Roseline Oluwaseun Ogundokun is an exemplary candidate for the Best Researcher Award. Her work not only advances the field of Computer Science but also positively impacts society through innovative solutions. Recognizing her achievements with this award would honor her contributions and inspire further excellence in research and education.

๐ŸŽ“ย Education

Roselineโ€™s academic journey began with a Bachelorโ€™s degree in Management Information Systems from Covenant University, followed by a Masterโ€™s in Computer Science from the University of Ilorin. She is currently pursuing dual PhDs in Computer Science and Multimedia Engineering, expected to be completed in 2022 and 2025, respectively. Her diverse educational background has equipped her with a strong foundation in both theoretical and practical aspects of technology, enabling her to contribute effectively to her field.

ย ๐Ÿ’ผ Experience

Roseline has extensive experience in academia, having worked at Landmark University since 2015 as a researcher, lecturer, and administrator. She has taught various courses, including Computer Programming and Software Engineering, while also supervising numerous undergraduate and postgraduate students in innovative research projects. Additionally, she has served as a visiting lecturer at Thomas Adewumi University and the Nigerian Army College of Education, contributing to the development of future tech leaders through her teaching and mentorship.

๐Ÿ… Awards and Honors

Roselineโ€™s commitment to research and education has earned her multiple accolades. She has been recognized for her contributions to machine learning and sustainable development, receiving awards from various educational institutions. Her research publications have garnered significant attention, leading to an impressive citation record, reflecting her influence in the academic community. She is also actively involved in mentorship programs, advocating for women’s participation in STEM fields.

๐ŸŒ Research Focus

Roselineโ€™s research interests are centered on artificial intelligence, computer vision, and deep learning. She is particularly focused on employing machine learning models to solve real-world problems across various sectors, including healthcare and telecommunications. Her work aims to advance the integration of technology in achieving sustainable development goals, particularly those related to industry, innovation, and infrastructure.

ย ๐Ÿ“– Publication Tob Notes

Predictive modelling of COVID-19 confirmed cases in Nigeria
Citation Count: 132
IoMT-based wearable body sensors network healthcare monitoring system
Citation Count: 99
Medical internet-of-things based breast cancer diagnosis using hyperparameter-optimized neural networks
Citation Count: 84
Application of big data with fintech in financial services
Citation Count: 78
An enhanced intrusion detection system using particle swarm optimization feature extraction technique
Citation Count: 62

Dr. Yunfei Chen | Multimedia Retrieval | Best Researcher Award

Dr. Yunfei Chen | Multimedia Retrieval | Best Researcher Awardย 

Dr. Yunfei Chen, Central south university, China

Yunfei Chen is a passionate research scholar specializing in multimedia hashing retrieval. He received his B.S. degree in Software Engineering from Henan University and his M.S. degree in Software Engineering from Harbin Engineering University. Currently, he is pursuing a Ph.D. at the Big Data Institute, School of Computer Science and Engineering at Central South University in Changsha, China. His research primarily focuses on Cross-Modal Retrieval, Computer Vision, and Pattern Recognition.Yunfei’s academic journey is marked by notable achievements. He has published significant papers in prestigious journals and conferences, including “Supervised Semantic-Embedded Hashing for Multimedia Retrieval” in Knowledge-Based Systems, and “Unsupervised Joint-Semantics Autoencoder Hashing for Multimedia Retrieval” presented at the International Conference on Neural Information Processing.

 

๐ŸŒ Professional Profile:

SCOPUS

Education and Experience

๐ŸŽ“ Yunfei Chen holds a B.S. degree in Software Engineering from Henan University and an M.S. degree in Software Engineering from Harbin Engineering University. He is currently pursuing a Ph.D. at the Big Data Institute, School of Computer Science and Engineering, Central South University in Changsha, China. His research interests are Cross-Modal Retrieval, Computer Vision, and Pattern Recognition.

Academic Achievements

๐Ÿ“š Yunfei has made significant contributions to the fields of multimedia retrieval and semantic hashing. His noteworthy publications include:

  1. ๐Ÿ“„ “Supervised Semantic-Embedded Hashing for Multimedia Retrieval.” Knowledge-Based Systems.
  2. ๐Ÿ“„ “Unsupervised Joint-Semantics Autoencoder Hashing for Multimedia Retrieval.” International Conference on Neural Information Processing. Singapore: Springer Nature Singapore, 2023: 318-330.
  3. ๐Ÿ“„ “S3ACH: Semi-Supervised Semantic Adaptive Cross-Modal Hashing.” International Conference on Neural Information Processing. Singapore: Springer Nature Singapore, 2023: 252-269.

Research, Innovations, and Extension

๐Ÿ” Research Projects: 1
๐Ÿ“ˆ Journals Published in SCI/SCIE Index: 1
๐Ÿ“– Journals Published in Scopus/Web of Science/PubMed: 1
๐Ÿ”ฌ Areas of Research: Multimedia Hashing Retrieval
๐Ÿ”ง Patents Published and Under Process: 3
๐Ÿ“ Editorial Appointments in Journals/Conferences: 3

Contributions to Research & Development

๐Ÿ”ฌ Yunfei Chen has made substantial contributions to Research & Development, Innovations, and Extension Activities within his field. His work primarily focuses on Cross-Modal Retrieval, Computer Vision, and Pattern Recognition. Through his research, Yunfei has developed innovative methods and frameworks that enhance the efficiency and effectiveness of multimedia retrieval systems.

๐ŸŒŸ One of his notable contributions is the development of Supervised Semantic-Embedded Hashing for Multimedia Retrieval, which has been recognized in the Knowledge-Based Systems journal. This method integrates semantic information into the hashing process, improving retrieval accuracy and speed.

๐Ÿ’ก Additionally, his work on Unsupervised Joint-Semantics Autoencoder Hashing, presented at the International Conference on Neural Information Processing, offers a novel approach to multimedia retrieval that does not require labeled data, making it highly adaptable and scalable.

Publication Top Notes:

Unsupervised Joint-Semantics Autoencoder Hashing for Multimedia Retrieval

S3ACH: Semi-Supervised Semantic Adaptive Cross-Modal Hashing

SPHASE: Multi-Modal and Multi-Branch Surgical Phase Segmentation Framework based on Temporal Convolutional Network