Role
Zeng Fan is a Research fellow on AI, machine learning and data science within CBIT at Nottingham Business School.
Career overview
Employer: Brunel University London
Role: Research fellow at Computer Science Department
He was primarily responsible for conducting extensive big data analysis and optimization, with a specific focus on feature and event detection, classification, and prediction within large-scale data environments. This involved employing both supervised and unsupervised modes to extract meaningful insights. One notable achievement includes the development of a sophisticated smart scheduling framework tailored for the mining industry. This framework facilitated optimization across all mining-related processes, including resource allocation, operational efficiency, and production enhancement. His overarching goal was to streamline operations by eliminating redundant data and enhancing analysis accuracy, ultimately achieving optimal big data utilization and efficiency.
Employer: London South Bank University
Role: Research Associate at Sustainable Innovation Centre
He was entrusted with the task of forging connections between London SMEs and universities to facilitate the commercialization of innovative clean technology products, processes, and services. His role involved providing sustainable businesses with access to essential knowledge, resources, and support necessary for their success. Central to his responsibilities was the engagement with SME sustainable development projects, where he played a pivotal role in fostering collaborations and facilitating growth. His expertise spanned various fields, including signal processing, the Internet of Things, electronics, and acoustics. He has successfully assisted 11 businesses, including notable ventures such as Measurable Energy, COYOSY, and Lockheed Technology, in their endeavours.