Majharul Alam Evan is a computer scientist currently pursuing a Master’s degree in Advanced Computer Science at the University of South Wales. He completed his Bachelor of Science in Computer Science from North South University, where he focused on advanced topics in machine learning, computer vision, and system development. During his undergraduate studies, he was involved in two significant research projects. The first project, titled "Aedes and Culex Mosquito Species Classification Using Custom CNN Method," involved designing a custom Convolutional Neural Network (CNN) model to classify mosquito species, Aedes and Culex, to aid in vector-borne disease management. The second project, "Comparative Study of YOLOv5 and Fast R-CNN on Nuclei Image Classification on the NuCLS Dataset," focused on analyzing the performance of YOLOv5 and Fast R-CNN models in the domain of biomedical imaging, particularly nuclei classification, emphasizing speed, accuracy, and scalability.

In addition to his research, he has professional experience as a System Developer at HSATE, where he contributed to the design, development, and maintenance of systems to enhance operational workflows and deliver scalable technical solutions. His current academic work at the University of South Wales involves delving deeper into deep learning, computer vision, and system architecture to solve real-world problems. His research interests include deep learning, biomedical imaging, object detection and classification models, and system optimization. Proficient in programming languages like Python and Java, and tools such as TensorFlow, PyTorch, OpenCV, YOLO, and Fast R-CNN, he combines technical expertise with a passion for impactful research and innovation.