Dr Fang Wang
Dr Fang Wang is a Senior Lecturer in the Department of Computer Science at Brunel University London. She received a PhD in artificial intelligence from the University of Edinburgh and worked as a senior researcher in the research centre of British Telecom (BT) Group, before she joined Brunel University London. Dr Wang has published a number of papers in books, journals and conferences and filed a series of patents.
Dr Wang is an established teacher and researcher in computer science and artificial intelligence. Her research areas include nature-inspired computing, agents, intelligent information processing, intelligent distributed computing, cyber security, smart cities (particularly smart transportation), intelligent education systems (e.g., education in the cloud) and cognitive science. She actively participated in a number of EU, EPSRC, BT long term research projects and received several technical awards, including Brightstar & Enterprise Venturing Technology and Entrepreneurship Award of BT, Gordon Radley Technical Premium Highly Commended award of BT and ACM Best Student Paper Award. She is on the editorial board of several international journals and serves on many conference program committees.
Dr Wang’s main research interest is artificial intelligence and its applications. This includes using nature-inspired techniques such as intelligent agents, swarm intelligence, evolutionary computing and neural networks to solve real world problems such as network optimisation, public transportation scheduling, adaptive learning, decentralised computing, intelligent user analysis, self-organising communities, and so on.
“My expertise are mainly in artificial intelligence and its applications, including machine learning, optimisation, data mining and data analysis. We are especially good at developing adaptive, self-organising and intelligent algorithms to improve system performance, by learning from histories and exploring (implicit) associations or information automatically, even in a large-scale, dynamically changing environment. The algorithms are usually specially designed to suit different customer needs and applications.”
- Network optimisation, including routing, network topology optimisation, resource management and many others on both computing networks and wireless sensor networks;
- Cyber security, including intelligent intrusion detection to detect and prevent various types of attacks on computing networks or Cloud;
- Intelligent education systems, including intelligent student profiling, automatic learning group formation, group recommendation and mobile education games development;
- e-Commerce, such as Business-to-Business (B2B) transaction network analysis based on data collected from eBay and automatic product recommendations to businessmen;
- User services including user experience analysis and learning, personalised user services and self-organising user communities
- Smart transportation systems associated with smart cities, including journey planning, arriving time and passenger number prediction and instant alerts.