Dr Liang Tian is currently an Associate Professor in the Department of Physics at Hong Kong Baptist University (HKBU). He also serves as an academic member in the State Key Laboratory of Environmental and Biological Analysis (HKBU) and the Institute of Computational and Theoretical Studies, and an associated member in the Shenzhen JL Computational Science and Applied Research Institute. Before joining HKBU, he was a postdoctoral fellow in the Harvard Medical School at Harvard University and a research fellow in the Channing Division of Network Medicine at Brigham and Women’s Hospital (Boston, USA). Dr Tian’s group performs cutting-edge interdisciplinary research on Complex Systems, Statistical Physics, and Biophysics by using various analytical, numerical, modelling, simulation, and data-mining and machine-learning techniques. The main topics include Human Microbiome and Community Ecology, Biological Big-data and Machine Learning, Complex Network: Structure and Dynamics, Data-mining in Traditional Chinese Medicine, Epidemiological Modelling and so on.

AI for Complex Systems

Dr. Tian’s group is dedicated to pioneering interdisciplinary research across a range of complex systems, where traditional analytic approaches falter due to a vast number of degrees of freedom with intricate interactions and structure involved. Our approach integrates principles and tools from statistical physics, network science, systems biology, and cutting-edge AI to develop a comprehensive understanding of these systems. At the core of our methodology is the identification and extraction of relevant statistics, dimensions, and features through advanced big-data mining and AI techniques. This allows us to construct statistical physics models and perform simulations that not only describe these systems accurately but also provide interpretative insights that are critical for further analysis and prediction. Our expertise uniquely positions us to reveal and understand the emergent properties and organizational principles of these systems, as well as the complex interplay between their structures and functions. Through this innovative research framework, Dr. Tian’s group aims to generate transformative insights and applications that will advance our understanding of complex systems in nature and technology.

Research Topics and Projects

(1) Human Microbiome and its Impact on Health and Disease

(2) AI for Traditional Chinese Medicine and Drug Discovery

(3) Complex Multimodal Brain Data and Computational Neuroscience

(4) Disease Transmission Modeling and Control

(5) Complex network and Nonlinear Systems: Structure and Dynamics

(6) Biological Big-data, Machine Learning, and Bioinformatics