Suoyi Tan

• PhD
• Associate Professor at National University of Defense Technology

Trajectory data is crucial for various applications but often suffers from incompleteness due to device limitations and diverse collection scenarios. Existing imputation methods rely on sparse trajectory or travel information, such as velocity, to infer missing points. However, these approaches assume that sparse trajectories retain essential behav...

Quantifying the significance of ties in preserving network connectivity is crucial for identifying weak ties, which often serve as bridges between communities, and for detecting community structures. However, accurately characterizing network connectivity and formalizing the relationship between weak ties and communities remain challenging. In this...

Human mobility serves as a fundamental component in shaping the contact networks through which infectious diseases propagate during pandemics. It significantly influences the spatial and temporal patterns of disease transmission among individuals. Traditional epidemic models often struggle to capture the complexity of these heterogeneous contact pa...

The analysis of connection strengths and distances in the mobility network is pivotal for delineating critical pathways, particularly in the context of epidemic propagation. Local connections that link proximate districts typically exhibit strong weights. However, ties that bridge distant regions with high levels of interaction intensity, termed st...

Understanding the dynamics of spreading and diffusion on networks is of critical importance for a variety of processes in real life. However, predicting the temporal evolution of diffusion on networks remains challenging as the process is shaped by network topology, spreading non-linearities, and heterogeneous adaptation behavior. In this study, we...

Accurate identification, quantification, and continual monitoring of carbon emissions constitute pivotal elements for proactive climate interventions. Conventional methodologies like direct measurement, including point-source assessments or remote sensing, often face challenges related to high costs or limited accuracy. Especially in low- and middl...

The coronavirus disease 2019 (COVID-19) pandemic and the measures taken by authorities to control its spread have altered human behavior and mobility patterns in an unprecedented way. However, it remains unclear whether the population response to a COVID-19 outbreak varies within a city or among demographic groups. Here, we utilized passively recor...

Understanding the dynamics of spreading and diffusion on networks is of critical importance for a variety of processes in real life. However, predicting the temporal evolution of diffusion on networks remains challenging as the process is shaped by network topology, spreading non-linearities, and heterogeneous adaptation behavior. In this study, we...

The coronavirus disease 2019 (COVID-19) pandemic and the measures taken by authorities to control its spread had altered human behavior and mobility patterns in an unprecedented way. However, it remains unclear whether the population response to a COVID-19 outbreak varies within a city or among demographic groups. Here we utilized passively recorde...

Background Public awareness of self-protection (PASP) is of vital importance in predicting the spread of infectious diseases. It can change the way people travel and socialize, thereby curbing the spread of the infectious diseases and mitigating its impact. The objective of this study is to explore the impact of PASP on the transmission of COVID-19...

Most existing studies assume that the network topology is already known when designing intervention strategies, which is difficult to achieve in practice. This paper focuses on network intervention with sampling information and assumes that the nodes are obtained by three typical graph sampling algorithms. The characteristics of sampling nodes’ deg...

Objective Contact tracing plays an essential role in mitigating the impact of an epidemic. During the COVID‐19 pandemic, studies of those who have been in close contact with confirmed cases offer critical insights to understand the epidemiological characteristics of SARS‐CoV‐2 better. This study conducts a meta‐analysis of existing studies' infecti...

Introduction Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the “Dynamic COVID-zero” strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods Informed by the daily number of passengers traveling between 367 pre...

Heterogeneous information network (HIN) has recently been receiving increasing attention in recommender systems due to its practicability in depicting data heterogeneity. The rich structural and semantic information embodied in the HIN can help mining latent features of users and items for recommendations. However, almost all existing HIN-based rec...

Background: The measurement and identification of changes in the social structure in response to an exceptional event like COVID-19 can facilitate a more informed public response to the pandemic and provide fundamental insights on how collective social processes respond to extreme events. Objective: In this study, we built a generalized framework f...

Understanding the spatial interactions of human mobility is crucial for urban planning, traffic engineering, as well as for the prevention and control of infectious diseases. Although many models have been developed to model human mobility, it is not clear whether such models could also capture the traveling mechanisms across different time periods...

2020 was an unprecedented year, with rapid and drastic changes in human mobility due to the COVID-19 pandemic. To understand the variation in commuting patterns among the Chinese population across stable and unstable periods, we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of populat...

Population migration is an essential medium for the spread of epidemic, which can accelerate localized outbreaks of disease into widespread epidemic. Large-scale population movements between different areas increase the risk of cross-infection and bring great challenges to epidemic prevention and control. As COVID-19 can spread rapidly through huma...

Close contacts with high-risk exposure to COVID-19 cases are more robust in statistics for inferring future development of COVID-19 epidemic. In Beijing, the proportion of close contact cases in newly confirmed cases had increased from about 50% at the end of January to nearly 100% in mid-February, indicating that contact tracing and quarantine mea...

Link prediction in complex networks has attracted much attention in recent years and most of work focuses on proposing more accurate prediction algorithms. In fact, “how difficultly the target network can be predicted” can be regarded as an important attribute of the network itself. In this paper it is intended to explain and characterize the link...

Evaluating the significance of nodes or links has always been an important issue in complex networks, and the definition of significance varies with different perspectives. The significance of nodes or links in maintaining the network connectivity is widely discussed due to its application in targeted attacks and immunization. In this paper, inspir...

Relationships between terrorists are amorphous, invisible, distributed and dispersed. The information of these networks is often incomplete and even erroneous. The key to disrupting the terrorists network is to find the critical nodes whose removal will lead to network collapse, however, most of the previous studies are based directly on the observ...

Dealing with the protection of critical infrastructures, many game-theoretic methods have been developed to study the strategic interactions between defenders and attackers. However, most game models ignore the interrelationship between different components within a certain system. In this paper, we propose a simultaneous-move attacker-defender gam...

The problem of network disintegration, which aims at identifying the critical nodes or edges whose removal will lead to a network collapse, has attracted much attention due to its wide applications. This paper focuses on the disintegration of directed networks. We propose a disintegration strategy based on tabu search. Experiments show that the dis...

Many real-world systems can be described by scale-free networks with power-law degree distributions. Scale-free networks show a “robust yet fragile” feature due to their heterogeneous degree distributions. We propose to enhance the structural robustness of scale-free networks against intentional attacks by changing the displayed network structure i...

Robustness and small-world effect are two crucial structural features of complex networks and have attracted increasing attention. However, little is known about the relation between them. Here we demonstrate that, there is a conflicting relation between robustness and small-world effect for a given degree sequence. We suggest that the robustness-o...

It has been recently proposed that natural connectivity can be used to efficiently characterize the robustness of complex networks. The natural connectivity has an intuitive physical meaning and a simple mathematical formulation, which corresponds to an average eigenvalue calculated from the graph spectrum. However, as a network model close to the...

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to...

The effects of three typical structural properties on invulnerability of complex network topologies are investigated based on the natural connectivity. The effect of degree distribution on invulnerability of complex network topologies is studied by generating complex networks with various degree distributions using mixing preferential attachment mo...