DIPPER Lab, KNUST, Ghana
Andrews Tang is a dedicated Computer Engineering graduate from Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana. With a deep passion for deep learning and computer vision, he has made significant contributions to various research fields, including blockchain technology, agriculture, and aviation safety. He has successfully designed innovative systems such as a decentralized food traceability platform and developed advanced machine learning models for detecting adulterated palm oil. Andrews continues to push the boundaries of AI through his role as a machine learning engineer and researcher, particularly focusing on predictive modeling and automation.
Profile
Scopus
Education 🎓
Andrews Tang graduated with a Bachelor of Science in Computer Engineering from KNUST in November 2022, where he achieved First Class Honours with a Cumulative Weighted Average (CWA) of 76.18% and a CGPA of 3.74/4.0 (WES evaluation). His academic excellence was recognized throughout his studies, and he earned several awards, such as the Excellent Student’s Award in 2020, 2022, and 2023.
Research Experience 🔬
Andrews’ research journey started during his undergraduate years at KNUST, where he worked in the Distributed IoT-Based Platforms, Privacy, and Edge-Intelligence Research (DIPPER) Lab. Notable projects include a blockchain-based food traceability system for Ghana’s agricultural supply chains and deep learning applications for detecting tomato diseases. His research further expanded with applications in palm oil adulteration detection, predictive modeling for aviation safety, and several machine learning-driven projects in agriculture and medical fields. He has continually advanced the scope of his research, aiming to develop AI solutions for societal challenges.
Research Interests 🔍
Andrews’ research interests lie primarily in Deep Learning and Computer Vision, areas he has passionately explored through various innovative projects. His focus has been on applying these technologies in practical, real-world problems, such as food safety, agricultural monitoring, and aviation safety systems. His research has significantly contributed to using AI to improve existing systems, as seen in his work on palm oil adulteration detection and predictive models for mineral ore recovery rates.
Awards 🏆
Andrews Tang has received several prestigious awards throughout his academic journey. These include:
- Excellent Student’s Award (2020, 2022, 2023) at KNUST
- Best Poster Award at the Deep Learning Indaba Conference (2023)
- Scholarship for BSc. Computer Engineering by the Ghana National Petroleum Corporation Foundation (2020)
- 2024 Member, Black in AI Fellowship (International)
Publications Top Notes 📚
“An Open and Fully Decentralised Platform for Safe Food Traceability”
2022 International Conference on Computational Science and Computational Intelligence (CSCI)
DOI: 10.1109/CSCI58124.2022.00092
“Assessing Blockchain and IoT Technologies for Agricultural Food Supply Chains in Africa: A Feasibility Analysis”
Heliyon
DOI: 10.1016/j.heliyon.2024.e34584
“AfroPALM – Afrocentric Palm Oil Adulteration Learning Models: An End-to-End Deep Learning Approach for Detection of Palm Oil Adulteration in West Africa”
LWT – Journal of Food Science and Technology
Preprint: SSRN
Revised Manuscript Under Review by Elsevier LWT Journal