Early Academic Pursuits

Andrews Tang’s academic journey began at the prestigious Kwame Nkrumah University of Science and Technology (KNUST) in Ghana, where he pursued a Bachelor of Science degree in Computer Engineering. A driven and focused scholar, Andrews consistently achieved high academic marks, earning First Class Honours with a CGPA of 3.74 out of 4.0, which corresponds to an impressive 76.18% Cumulative Weighted Average (CWA). His performance not only demonstrated his dedication to excellence but also solidified his foundational knowledge in engineering principles, mathematics, and computer science—skills he would later leverage in research. Andrews’ early interest in computer vision and deep learning set him apart, leading him to specialize in these advanced fields of study. Through rigorous coursework and early exposure to complex computational concepts, he built a solid academic background that would fuel his research ambitions in both blockchain and artificial intelligence.

Professional Endeavors

After excelling academically, Andrews immersed himself in hands-on research, working with KNUST’s Distributed IoT-based Platforms, Privacy, and Edge-Intelligence Research (DIPPER) Lab. Here, he first served as an Undergraduate Student Researcher, focusing on blockchain-based decentralized systems. His initial project, aimed at developing a fully decentralized food traceability system, addressed critical issues in Ghana’s agricultural supply chains. Utilizing platforms like Hyperledger Fabric, Docker, and Docker Compose, Andrews designed a system that enhances transparency and security in food distribution—an innovation that speaks directly to Ghana’s agricultural priorities. In addition, he furthered his expertise as a Research Assistant, working on a deep learning project that applied computer vision to assess the condition of tomatoes. By integrating tools like MobileNetV2 and Trident-YOLO, Andrews developed models that accurately classified tomato diseases, and, by combining them with Support Vector Regression (SVR) models, he created comprehensive solutions for agricultural quality control.

Contributions and Research Focus

Throughout his career, Andrews has contributed meaningfully to diverse fields, including computer vision, blockchain, and machine learning. One of his notable achievements was developing the AfroPALM collective, a set of deep learning models for detecting adulteration in red palm oil. Working with DIPPER Lab and the Responsible Artificial Intelligence Lab (RAIL), he collected data from multiple Ghanaian regions and applied deep learning methods like GhostNet and SqueezeNet to create AfroPALM-Custom. This model achieved an impressive test accuracy and F1-score exceeding 90%, setting new standards for food safety and quality control in Africa. Furthermore, Andrews ventured into aviation safety with his recent project on predictive modeling for the Instrument Landing System (ILS). By applying the CatBoost classifier and leveraging Python for predictive analytics, he improved ILS accuracy under low-visibility conditions, thus addressing significant challenges in aviation safety.

Accolades and Recognition

Andrews Tang’s research has earned him recognition within academic and professional circles. His contributions to computer engineering, particularly in creating practical solutions for real-world issues, have positioned him as a promising young researcher. His publication on blockchain applications in food traceability received attention for its innovative use of decentralized platforms, demonstrating his commitment to applying academic knowledge to critical, real-world problems. Andrews’ work on the AfroPALM models, with its impressive performance metrics, has established him as a researcher capable of pioneering new approaches in machine learning and food quality analysis.

Impact and Influence

Andrews’ work extends beyond academic achievement; it represents impactful contributions to Ghana’s agriculture and food industries, aviation, and public safety. His blockchain-based food traceability project not only supports Ghana’s agricultural development but also encourages transparency and efficiency in food distribution systems—a necessity for health and economic security. Similarly, his work on detecting adulteration in red palm oil helps to protect consumers from unsafe products while preserving the economic integrity of local producers. His aviation research on ILS reliability also underscores his commitment to public safety, showcasing the far-reaching impact of his work in various sectors.

Legacy and Future Contributions

Looking to the future, Andrews aims to continue advancing research in deep learning and computer vision, with a particular focus on their applications in sectors crucial to Ghana’s development. His recent ventures into machine learning for predictive modeling in aviation safety suggest an evolving focus on high-stakes industries that rely heavily on accuracy and reliability. Andrews envisions expanding his research to include broader aspects of artificial intelligence, with a goal to address challenges not only in agriculture and aviation but also in healthcare, environmental monitoring, and energy sectors.

By focusing on practical, solution-oriented research, Andrews Tang is building a legacy of innovation and dedication to societal improvement. His journey from a dedicated student to a visionary researcher reflects his passion for harnessing technology to tackle complex problems, paving the way for a future of meaningful contributions in the fields of AI, machine learning, and blockchain.

Notable Publications