Brain Inspired Computing, Artificial Intelligence,Machine Learning and Complex Networks
1.Brain Inspired Computing, Artificial Intelligence and Machine Learning: Designing smart and energy-efficient computing systems inspired from the recent research progress in the human brain and theories of artificial intelligence and machine learning.
2.Complex Networks: Studying the nature of internal/external interactions in real-world networks including social, economic, biological, ecological, and technological networks that display substantial non-trivial topological features, which are essential for the investigation of the control profiles of real life complex networks.
Dr. Li has published about 50 SCI indexed Journal papers (including IEEE TSP, IEEE TNNLS, IEEE TAC, Automatica, IEEE TCYB, Scientific Reports and Frontiers in Neuroscience and so on) and 20 conference papers. He services as Editorial board member of Frontiers in Neuroscience (since 2017), and the Journal of Control and Decision (2017-2020). He also services as a reviewer for a number of international journals and has been actively involved in professional services such as serving as an International Technical Program Committee member, and a Track Chair for international conferences (IEEE ICIEA, IEEE CCDC) since 2014.