Professor , Prince Sattam bin abdalaziz university , Saudi Arabia
Dr. Reem Aljuaidi ๐ฉโ๐ซ is an accomplished Assistant Professor in the Information Systems Department at Prince Sattam bin Abdulaziz University, Saudi Arabia ๐ธ๐ฆ. With a strong foundation in computer science and a specialization in computer vision, big data, and data analytics ๐๐ง , she has contributed to cutting-edge research in visual place recognition and intelligent geolocation systems. Dr. Aljuaidi earned her PhD from Trinity College Dublin ๐ฎ๐ช and has since become a leading figure in Saudi academia, recognized for her impactful publications and conference presence ๐ค๐. Fluent in Arabic and English ๐ธ๐ฆ๐บ๐ธ, she bridges local innovation with global insight. In addition to her academic work, she serves as a professional trainer and workshop speaker, contributing to the digital transformation and educational empowerment of the region ๐ก๐. Her scholarly excellence and innovative spirit have earned her multiple awards, highlighting her role as a rising star in AI-driven research ๐๐ค.
Professional Profile
SCOPUS
Education & Experience
Dr. Aljuaidiโs educational journey showcases her commitment to excellence ๐๐. She completed her PhD in Computer Science at Trinity College Dublin (2017โ2022) ๐ฎ๐ช, preceded by a Masterโs in Data Analytics from the National University of Ireland, Galway (2016โ2017) ๐. Her academic path began with a Bachelor’s degree from King Saud University (2005โ2009) in Saudi Arabia ๐ธ๐ฆ, where she laid the groundwork for a remarkable research career. She also enhanced her academic English skills at Washington State University, USA (2014โ2015) ๐บ๐ธ. Her professional experience includes serving as an Assistant Professor (2023โpresent) and former Instructor (2010โ2014) at Prince Sattam bin Abdulaziz University ๐ซ. She is also a certified trainer with Jadeer International Education and Training Company (2023โpresent), where she fosters future tech leaders ๐ฉโ๐ป๐. This blend of academic and applied experience defines her dynamic contribution to higher education and industry-oriented learning ๐งฉ๐.
Professional Development
Dr. Reem Aljuaidi has actively participated in professional development initiatives that reflect her evolving impact in both academic and technological domains ๐๐. She was a speaker at the Women in Data Science workshop in Riyadh (2024) ๐ฉโ๐ป, and also presented at the International Operatenance Conference in Arab Countries (2022) ๐. She participated in the Library Hackathon Challenge hosted by the Libraries Authority (2024) ๐ป๐, showcasing her creative data problem-solving skills. Her research proposal was selected for the Technology Foresight and Digital Economy Research Award for GCC countries (2024) ๐๐. As a commercial trainer, she contributes to real-world digital skill advancement, combining research insights with hands-on knowledge transfer ๐ ๏ธ๐๏ธ. Her proactive learning journey highlights her role as not only an academic but also a mentor, innovator, and community advocate in the digital transformation space ๐ผ๐ฏ. Dr. Aljuaidi continuously embraces learning and leadership in every forum she enters ๐๐ง .
Research Focus
Dr. Aljuaidiโs research primarily revolves around Computer Vision ๐๏ธ๐ป, Big Data Analytics ๐, and Data-Driven AI Systems ๐ค. Her expertise lies in designing intelligent models for Visual Place Recognition and Geolocation Systems, which involve hybrid feature prediction, image processing, and machine learning pipelines ๐ท๐ก. She has published research on using Google Street View and unique feature extraction for efficient visual retrieval, highlighting her contribution to smarter, location-aware AI systems ๐ง ๐. Through her interdisciplinary approach, she integrates computer vision algorithms with real-world applications such as urban mapping, autonomous systems, and digital infrastructure planning ๐๏ธ๐. Her work aligns with global trends in AI for Smart Cities and Data-Enhanced Automation, making her a pivotal figure in Saudi Arabiaโs tech-driven future ๐ธ๐ฆ๐. Dr. Aljuaidiโs research continues to impact conferences and journals, bridging theory and practice for both academic advancement and applied innovation ๐๐ผ.
Awards & Honors
Dr. Reem Aljuaidi has earned several prestigious accolades that underline her innovation and scholarly impact ๐๐. She won the Best Research Paper award at the 30th Irish Signals and Systems Conference (ISSC) in 2019 ๐๐, a testament to her excellence in computer vision research. In 2024, she was honored with the Best Idea in the Social Track at the Family Affairs Council Competition for her forward-thinking digital concepts ๐ช๐ก. Her proposal was accepted into the Technology Foresight and Digital Economy Research Award program for GCC countries (2024), further confirming her as a regional research leader ๐๐ฌ. She was also a featured speaker at major events including Women in Data Science Riyadh and the International Operatenance Conference ๐๐ค. These accolades reflect not just academic achievement, but her contributions to digital empowerment and societal innovation across multiple platforms ๐ง ๐.
Publication Top Notes
1. Mini-batch VLAD for Visual Place Retrieval
Authors: R. Aljuaidi, J. Su, R. Dahyot
Conference: 30th Irish Signals and Systems Conference (ISSC), 2019
Pages: 1โ6
Summary:
This paper introduces an improved visual place retrieval method using mini-batch VLAD (Vector of Locally Aggregated Descriptors), which enhances scalability and computational efficiency. By optimizing feature aggregation in mini-batches, the model improves accuracy in identifying previously visited places, a critical task in robotics and autonomous navigation ๐บ๏ธ๐ค.
2. An Efficient Visual Place Recognition System by Predicting Unique Features
Authors: R. Aljuaidi, M. Manzke
Conference: 5th International Conference on Computer Science and Software Engineering (ICCSSE), 2022
Summary:
This paper presents a novel method to predict unique image features for more efficient place recognition systems. By identifying and focusing on distinctive features, the proposed system significantly enhances recognition speed and precision, especially in large-scale environments. Applications include autonomous driving, AR navigation, and smart surveillance ๐๐.
3. Predicting Good Features Using a Hybrid Feature for Visual Geolocation System
Authors: R. Aljuaidi, M. Manzke
Conference: 14th International Conference on Digital Image Processing (ICDIP), 2022
Summary:
This research combines multiple feature extraction techniques into a hybrid model to improve the reliability of visual geolocation. The paper demonstrates how the fusion of texture, color, and shape descriptors can produce higher location recognition accuracy, aiding in urban planning and smart tourism systems ๐๏ธ๐ท.
4. Efficient Visual Place Retrieval System Using Google Street View
Authors: R. Aljuaidi, R. Dahyot
Conference: Irish Machine Vision and Image Processing Conference (IMVIP), 2020
Summary:
In this study, the authors leverage publicly available Google Street View imagery to train and test an effective place retrieval system. The model utilizes visual cues from street-level data, providing practical applications in geolocation services, mapping, and augmented reality navigation ๐บ๏ธ๐ธ.
Conclusion
Dr. Reem Aljuaidi exemplifies what a Best Researcher Award representsโoriginality, depth, and practical impact in research. Her consistent contributions to computer science, academic leadership, and innovation in AI-driven solutions for geolocation and visual analysis clearly position her as a leading researcher and an ideal recipient for this honor.