HKU Musketeers Foundation Institute of Data Science (HKU-IDS) proudly presents the “HKU-IDS Scholar Seminar Series” which will run through the year of 2022-23. The seminar series will feature the HKU-IDS new recruits under HKU-100 Professoriate Recruitment Campaign forming the backbone for the Institute’s cross-disciplinary collaboration. These young talents are co-hosted by IDS and different Departments including Computer Science, Electrical and Electronic Engineering, Architecture, Pharmacy and Pharmacology, Industrial and Manufacturing Systems Engineering and Mathematics.
Title: Complex network inference: Efficient algorithms and insights for urban spatial segregation
Speaker: Dr. Alec Kirkley, the Musketeers Foundation Institute of Data Science and Department of Urban Planning and Design, HKU
Moderator: Professor Anthony Yeh, Chair Professor, Department of Urban Planning and Design, HKU
Date: August 19, 2022
Time: 10:00 – 11:00am
In this seminar, the speaker will give an overview of two recent projects he has been involved in, during which new efficient statistical inference algorithms for complex network data are developed. A belief propagation algorithm for computing one-point marginals and other quantities of interest in probabilistic graphical models on networks with short loops will first be described. This algorithm provides a significant accuracy improvement over standard belief propagation for graphical models over highly clustered networks, which are ubiquitous in complex systems research, and runs in only a fraction of the time it takes to run standard Monte Carlo sampling. The speaker will demonstrate its capabilities using the Ising model from statistical physics as an example system. He will then move on to discuss a fast parameter-free algorithm to perform regionalization, spatially contiguous clustering, over areal units with distributional metadata such as those sampled for census analysis. The problem of regionalization is viewed as one of data compression, optimizing an objective derived using purely combinatorial arguments and the minimum description length principle. The speaker will further demonstrate how the method is capable of recovering planted spatial clusters in noisy synthetic data, and that it can meaningfully coarse-grain real demographic data to provide new insights about urban spatial segregation. Using the description length formulation, it is found that spatial ethnoracial data in metropolitan areas across the U.S. has become more difficult to compress over the period from 1980 to 2010, reflecting the rising complexity of urban segregation patterns of these metros. Increasing ethnoracial diversity at small spatial scales within these metros is identified as a major contributor to this lower data compressibility, while changes in large scale ethnoracial clustering and population are not significant factors.
Prof Anthony Yeh is currently the Chan To Haan Professor in Urban Planning and Design and Chair Professor in Urban Planning and Geographic Information Systems of the Department of Urban Planning and Design and Director of the Geographic Information Systems (GIS) Research Centre of The University of Hong Kong. His main areas of specialization are the applications of geographic information systems in urban and regional planning and smart cities and urban planning and development in Hong Kong, China, and SE Asia. He has also been serving in multiple positions in regional and local statutory organisations, as well as the Hong Kong SAR Government. For full biography of Professor Yeh, please browse his website here.
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