Academic Profile : Faculty

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Assoc Prof Mao Kezhi
Associate Professor, School of Electrical & Electronic Engineering
Dr. Mao obtained his BEng, MEng and PhD from Jinan University, Northeastern University, and University of Sheffield in 1989, 1992 and 1998 respectively. Since obtaining his PhD, he has been working at School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is an Associate Professor. Dr. Mao's expertise spans several subfields of artificial intelligence (AI), including machine learning, computer vision (CV), natural language processing (NLP), and information fusion. In recent years, he has directed his research focus toward the dynamic and transformative domain of NLP such as large language models (LLM).

As the lead Principal Investigator, Dr. Mao has successfully completed over a dozen funded projects that span the vast landscape of AI. As a passionate advocate of translational research, Dr. Mao and his team developed and delivered a range of intelligent systems and tools to government agencies and industries, enriched with AI-driven solutions.

Beyond his research and development endeavors, Dr. Mao is active in conducting consultancy work in the AI landscape. He advised several multinational corporations on the direction of AI research in the business world, emphasizing the practical applications of the state-of-the-art technologies.

For professional services, he is now serving as the Editorial Board Member of Neural Networks, Academic Editor of Computational Intelligence and Neuroscience. He served as the General Chair, Co-Chair, Invited Panelist, and Invited Speaker of several international conferences.

He is listed among the Top 2% Scientists Worldwide by Stanford University. Within the realm of AI, his research ranks in the top 0.5%.
Machine Learning and Deep Learning for Big Data, Natural Language Processing, Image/Video Processing and Analysis, Information Fusion
 
  • WP 1.2 Accuracy & Resolution Enhancement for Large-Volume Robot Workspace Digitalization
Courses Taught
EE7207 Neural and Fuzzy Systems, EE6227 Genetic Algorithms and Machine Learning, EE4285 Computational Intelligence, EE4903 Physiological Systems Analysis.
 
Supervision of PhD Students
Supervised 15 Postdoctoral Reserarch Fellows and Research Engineers, 30 PhD and MEng students and over 80 MSc students